This project is focused on advanced statistical methods and machine learning techniques. It includes various exercises, solutions, and resources to help you understand and implement these concepts effectively.
Here is a list of resources included in this project:
-
Advanced Statistical Methods
- [Selecting the Number of Clusters](Part_5_Advanced_Statistical_Methods_(Machine_Learning)/S38_L259/Selecting the number of clusters_with_comments.ipynb): A notebook that discusses methods for determining the optimal number of clusters in clustering algorithms.
- [Clustering Categorical Data - Solution](Part_5_Advanced_Statistical_Methods_(Machine_Learning)/S38_L258/Clustering Categorical Data - Solution.ipynb): A solution notebook for clustering categorical data with explanations.
- [Species Segmentation with Cluster Analysis](Part_5_Advanced_Statistical_Methods_(Machine_Learning)/S38_L268/Species Segmentation with Cluster Analysis Part 2 - Exercise.ipynb): An exercise focused on segmenting species using clustering techniques.
-
Deep Learning
- TensorFlow Audiobooks - Outlining the Model: A notebook outlining the model for audiobooks using TensorFlow.
- TensorFlow Audiobooks - Preprocessing: A notebook detailing the preprocessing steps for the audiobooks dataset.
-
Logistic Regression
- [Building a Logistic Regression - Exercise](Part_5_Advanced_Statistical_Methods_(Machine_Learning)/S36_L238/Building a Logistic Regression - Exercise.ipynb): An exercise to build a logistic regression model based on bank marketing data.
- [Understanding Logistic Regression Tables - Exercise](Part_5_Advanced_Statistical_Methods_(Machine_Learning)/S36_L241/Understanding Logistic Regression Tables - Exercise.ipynb): A notebook that helps understand the output tables from logistic regression.
To set up the project, clone the repository and install the required packages:
git clone https://github.com/UTSAVS26/PyVerse
cd PyVerse
pip install -r requirements.txte:/Data Science Course 2021/
├── FAQ_The_Data_Science_Course.pdf
├── Part_1_Intro_to_Data_and_Data_Science/
│ ├── 365-DataScience-Diagram.pdf
│ └── 365-DataScience.png
├── Part_2_Probability/
│ ├── Additional Exercises Combinatorics Solutions.pdf
│ ├── Additional Exercises Combinatorics.pdf
│ ├── CDS_2017-2018 Hamilton.pdf
│ ├── Combinations With Repetition.pdf
│ ├── Course Notes - Basic Probability.pdf
│ ├── Course Notes - Bayesian Inference.pdf
│ ├── Course Notes - Combinatorics.pdf
│ ├── Course Notes - Probability Distributions.pdf
│ ├── Dataset for practice/
│ │ ├── Customers_Membership (post).xlsx
│ │ ├── Customers_Membership.xlsx
│ │ ├── Daily Views (post).xlsx
│ │ ├── Daily Views.xlsx
│ │ ├── FIFA19 (post).csv
│ │ └── FIFA19.csv
│ ├── Normal Distribution - Expected Value and Variance.pdf
│ ├── Poisson - Expected Value and Variance.pdf
│ ├── Solving Integrals.pdf
│ └── Symmetry Explained.pdf
├── Part_3_Statistics/
│ ├── S14_L71/
│ │ ├── Course-notes-descriptive-statistics.pdf
│ │ └── Glossary.xlsx
│ ├── S15_L72/
│ │ └── Course-notes-descriptive-statistics.pdf
│ ├── S15_L73/
│ │ └── 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx
│ ├── S15_L74/
│ │ ├── 2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx
│ │ └── 2.3.Categorical-variables.Visualization-techniques-exercise.xlsx
│ ├── S15_L75/
│ │ └── 2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx
│ ├── S15_L76/
│ │ ├── 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx
│ │ └── 2.4.Numerical-variables.Frequency-distribution-table-exercise.xlsx
│ ├── S15_L77/
│ │ └── 2.5.The-Histogram-lesson.xlsx
│ ├── S15_L78/
│ │ ├── 2.5.The-Histogram-exercise-solution.xlsx
│ │ └── 2.5.The-Histogram-exercise.xlsx
│ ├── S15_L79/
│ │ └── 2.6.Cross-table-and-scatter-plot.xlsx
│ ├── S15_L80/
│ │ ├── 2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx
│ │ └── 2.6.Cross-table-and-scatter-plot-exercise.xlsx
│ ├── S15_L81/
│ │ └── 2.7.Mean-median-and-mode-lesson.xlsx
│ ├── S15_L82/
│ │ ├── 2.7.Mean-median-and-mode-exercise-solution.xlsx
│ │ └── 2.7.Mean-median-and-mode-exercise.xlsx
│ ├── S15_L83/
│ │ └── 2.8.Skewness-lesson.xlsx
│ ├── S15_L84/
│ │ ├── 2.8.Skewness-exercise-solution.xlsx
│ │ └── 2.8.Skewness-exercise.xlsx
│ ├── S15_L85/
│ │ └── 2.9.Variance-lesson.xlsx
│ ├── S15_L86/
│ │ ├── 2.9.Variance-exercise-solution.xlsx
│ │ └── 2.9.Variance-exercise.xlsx
│ ├── S15_L87/
│ │ └── 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx
│ ├── S15_L88/
│ │ ├── 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx
│ │ └── 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx
│ ├── S15_L89/
│ │ └── 2.11.Covariance-lesson.xlsx
│ ├── S15_L90/
│ │ ├── 2.11.Covariance-exercise-solution.xlsx
│ │ └── 2.11.Covariance-exercise.xlsx
│ ├── S15_L92/
│ │ ├── 2.12.Correlation-exercise-solution.xlsx
│ │ └── 2.12.Correlation-exercise.xlsx
│ ├── S16_L93/
│ │ └── 2.13.Practical-example.Descriptive-statistics-lesson.xlsx
│ ├── S16_L94/
│ │ ├── 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx
│ │ └── 2.13.Practical-example.Descriptive-statistics-exercise.xlsx
│ ├── S17_L95/
│ │ └── Course-notes-inferential-statistics.pdf
│ ├── S17_L96/
│ │ ├── 3.2.What-is-a-distribution-lesson.xlsx
│ │ └── Course-notes-inferential-statistics.pdf
│ ├── S17_L98/
│ │ └── 3.4.Standard-normal-distribution-lesson.xlsx
│ ├── S17_L99/
│ │ ├── 3.4.Standard-normal-distribution-exercise-solution.xlsx
│ │ └── 3.4.Standard-normal-distribution-exercise.xlsx
│ ├── S18_L104/
│ │ ├── 3.9.Population-variance-known-z-score-lesson.xlsx
│ │ └── 3.9.The-z-table.xlsx
│ ├── S18_L105/
│ │ ├── 3.9.Population-variance-known-z-score-exercise-solution.xlsx
│ │ ├── 3.9.Population-variance-known-z-score-exercise.xlsx
│ │ └── 3.9.The-z-table.xlsx
│ ├── S18_L108/
│ │ ├── 3.11.Population-variance-unknown-t-score-lesson.xlsx
│ │ └── 3.11.The-t-table.xlsx
│ ├── S18_L109/
│ │ ├── 3.11.Population-variance-unknown-t-score-exercise-solution.xlsx
│ │ └── 3.11.Population-variance-unknown-t-score-exercise.xlsx
│ ├── S18_L111/
│ │ ├── 3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx
│ │ └── COALESCE-Preamble.pdf
│ ├── S18_L112/
│ │ ├── 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx
│ │ └── 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx
│ ├── S18_L113/
│ │ └── 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx
│ ├── S18_L114/
│ │ ├── 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx
│ │ └── 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx
│ ├── S18_L115/
│ │ └── 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx
│ ├── S18_L116/
│ │ ├── 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx
│ │ └── 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx
│ ├── S19_L118/
│ │ └── 3.17.Practical-example.Confidence-intervals-lesson.xlsx
│ ├── S19_L119/
│ │ ├── 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx
│ │ └── 3.17.Practical-example.Confidence-intervals-exercise.xlsx
│ ├── S20_L120/
│ │ └── Course-notes-hypothesis-testing.pdf
│ ├── S20_L122/
│ │ └── Course-notes-hypothesis-testing.pdf
│ ├── S20_L124/
│ │ └── 4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx
│ ├── S20_L125/
│ │ ├── 4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx
│ │ └── 4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx
│ ├── S20_L126/
│ │ └── Online-p-value-calculator.pdf
│ ├── S20_L127/
│ │ └── 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx
│ ├── S20_L128/
│ │ ├── 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx
│ │ └── 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx
│ ├── S20_L129/
│ │ └── 4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx
│ ├── S20_L130/
│ │ ├── 4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx
│ │ └── 4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx
│ ├── S20_L131/
│ │ └── 4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx
│ ├── S20_L132/
│ │ ├── 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx
│ │ └── 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx
│ ├── S20_L133/
│ │ └── 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx
│ ├── S20_L134/
│ │ ├── 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx
│ │ └── 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx
│ ├── S21_L135/
│ │ └── 4.10.Hypothesis-testing-section-practical-example.xlsx
│ └── S21_L136/
│ ├── 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx
│ └── 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx
├── Part_4_Python/
│ ├── S23_L143/
│ │ ├── Python 2/
│ │ │ ├── Variables - Exercise_Py2.ipynb
│ │ │ ├── Variables - Lecture_Py2.ipynb
│ │ │ └── Variables - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Variables - Exercise_Py3.ipynb
│ │ ├── Variables - Lecture_Py3.ipynb
│ │ └── Variables - Solution_Py3.ipynb
│ ├── S23_L144/
│ │ ├── Python 2/
│ │ │ ├── Numbers and Boolean Values - Exercise_Py2.ipynb
│ │ │ ├── Numbers and Boolean Values - Lecture_Py2.ipynb
│ │ │ └── Numbers and Boolean Values - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Numbers and Boolean Values - Exercise_Py3.ipynb
│ │ ├── Numbers and Boolean Values - Lecture_Py3.ipynb
│ │ └── Numbers and Boolean Values - Solution_Py3.ipynb
│ ├── S23_L145/
│ │ ├── Python 2/
│ │ │ ├── Strings - Exercise_Py2.ipynb
│ │ │ ├── Strings - Lecture_Py2.ipynb
│ │ │ └── Strings - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Strings - Exercise_Py3.ipynb
│ │ ├── Strings - Lecture_Py3.ipynb
│ │ └── Strings - Solution_Py3.ipynb
│ ├── S24_L146/
│ │ ├── Python 2/
│ │ │ ├── Arithmetic Operators - Exercise_Py2.ipynb
│ │ │ ├── Arithmetic Operators - Lecture_Py2.ipynb
│ │ │ └── Arithmetic Operators - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Arithmetic Operators - Exercise_Py3.ipynb
│ │ ├── Arithmetic Operators - Lecture_Py3.ipynb
│ │ └── Arithmetic Operators - Solution_Py3.ipynb
│ ├── S24_L147/
│ │ ├── Python 2/
│ │ │ ├── The Double Equality Sign - Exercise_Py2.ipynb
│ │ │ ├── The Double Equality Sign - Lecture_Py2.ipynb
│ │ │ └── The Double Equality Sign - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── The Double Equality Sign - Exercise_Py3.ipynb
│ │ ├── The Double Equality Sign - Lecture_Py3.ipynb
│ │ └── The Double Equality Sign - Solution_Py3.ipynb
│ ├── S24_L148/
│ │ ├── Python 2/
│ │ │ ├── Reassign Values - Exercise_Py2.ipynb
│ │ │ ├── Reassign Values - Lecture_Py2.ipynb
│ │ │ └── Reassign Values - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Reassign Values - Exercise_Py3.ipynb
│ │ ├── Reassign Values - Lecture_Py3.ipynb
│ │ └── Reassign Values - Solution_Py3.ipynb
│ ├── S24_L149/
│ │ ├── Python 2/
│ │ │ └── Add Comments - Lecture_Py2.ipynb
│ │ └── Python 3/
│ │ └── Add Comments - Lecture_Py3.ipynb
│ ├── S24_L150/
│ │ ├── 0.2.1 Variables/
│ │ │ ├── Python 2/
│ │ │ │ ├── Variables - Exercise_Py2.ipynb
│ │ │ │ ├── Variables - Lecture_Py2.ipynb
│ │ │ │ └── Variables - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── Variables - Exercise_Py3.ipynb
│ │ │ ├── Variables - Lecture_Py3.ipynb
│ │ │ └── Variables - Solution_Py3.ipynb
│ │ ├── 0.2.2 Numbers and Boolean Values/
│ │ │ ├── Python 2/
│ │ │ │ ├── Numbers and Boolean Values - Exercise_Py2.ipynb
│ │ │ │ ├── Numbers and Boolean Values - Lecture_Py2.ipynb
│ │ │ │ └── Numbers and Boolean Values - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── Numbers and Boolean Values - Exercise_Py3.ipynb
│ │ │ ├── Numbers and Boolean Values - Lecture_Py3.ipynb
│ │ │ └── Numbers and Boolean Values - Solution_Py3.ipynb
│ │ ├── 0.2.3 Strings/
│ │ │ ├── Python 2/
│ │ │ │ ├── Strings - Exercise_Py2.ipynb
│ │ │ │ ├── Strings - Lecture_Py2.ipynb
│ │ │ │ └── Strings - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── Strings - Exercise_Py3.ipynb
│ │ │ ├── Strings - Lecture_Py3.ipynb
│ │ │ └── Strings - Solution_Py3.ipynb
│ │ ├── 0.3.1 Arithmetic Operators/
│ │ │ ├── Python 2/
│ │ │ │ ├── Arithmetic Operators - Exercise_Py2.ipynb
│ │ │ │ ├── Arithmetic Operators - Lecture_Py2.ipynb
│ │ │ │ └── Arithmetic Operators - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── Arithmetic Operators - Exercise_Py3.ipynb
│ │ │ ├── Arithmetic Operators - Lecture_Py3.ipynb
│ │ │ └── Arithmetic Operators - Solution_Py3.ipynb
│ │ ├── 0.3.2 The Double Equality Sign/
│ │ │ ├── Python 2/
│ │ │ │ ├── The Double Equality Sign - Exercise_Py2.ipynb
│ │ │ │ ├── The Double Equality Sign - Lecture_Py2.ipynb
│ │ │ │ └── The Double Equality Sign - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── The Double Equality Sign - Exercise_Py3.ipynb
│ │ │ ├── The Double Equality Sign - Lecture_Py3.ipynb
│ │ │ └── The Double Equality Sign - Solution_Py3.ipynb
│ │ ├── 0.3.3 Reassign Values/
│ │ │ ├── Python 2/
│ │ │ │ ├── Reassign Values - Exercise_Py2.ipynb
│ │ │ │ ├── Reassign Values - Lecture_Py2.ipynb
│ │ │ │ └── Reassign Values - Solution_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ ├── Reassign Values - Exercise_Py3.ipynb
│ │ │ ├── Reassign Values - Lecture_Py3.ipynb
│ │ │ └── Reassign Values - Solution_Py3.ipynb
│ │ ├── 0.3.4 Add Comments/
│ │ │ ├── Python 2/
│ │ │ │ └── Add Comments - Lecture_Py2.ipynb
│ │ │ └── Python 3/
│ │ │ └── Add Comments - Lecture_Py3.ipynb
│ │ ├── Python 2/
│ │ │ ├── Line Continuation - Exercise_Py2.ipynb
│ │ │ ├── Line Continuation - Lecture_Py2.ipynb
│ │ │ └── Line Continuation - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Line Continuation - Exercise_Py3.ipynb
│ │ ├── Line Continuation - Lecture_Py3.ipynb
│ │ └── Line Continuation - Solution_Py3.ipynb
│ ├── S24_L151/
│ │ ├── Python 2/
│ │ │ ├── Indexing Elements - Exercise_Py2.ipynb
│ │ │ ├── Indexing Elements - Lecture_Py2.ipynb
│ │ │ └── Indexing Elements - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Indexing Elements - Exercise_Py3.ipynb
│ │ ├── Indexing Elements - Lecture_Py3.ipynb
│ │ └── Indexing Elements - Solution_Py3.ipynb
│ ├── S24_L152/
│ │ ├── Python 2/
│ │ │ ├── Structure Your Code with Indentation - Exercise_Py2.ipynb
│ │ │ ├── Structure Your Code with Indentation - Lecture_Py2.ipynb
│ │ │ └── Structure Your Code with Indentation - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Structure Your Code with Indentation - Exercise_Py3.ipynb
│ │ ├── Structure Your Code with Indentation - Lecture_Py3.ipynb
│ │ └── Structure Your Code with Indentation - Solution_Py3.ipynb
│ ├── S25_L153/
│ │ ├── Python 2/
│ │ │ ├── Comparison Operators - Exercise_Py2.ipynb
│ │ │ ├── Comparison Operators - Lecture_Py2.ipynb
│ │ │ └── Comparison Operators - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Comparison Operators - Exercise_Py3.ipynb
│ │ ├── Comparison Operators - Lecture_Py3.ipynb
│ │ └── Comparison Operators - Solution_Py3.ipynb
│ ├── S25_L154/
│ │ ├── Python 2/
│ │ │ ├── Logical and Identity Operators - Exercise_Py2.ipynb
│ │ │ ├── Logical and Identity Operators - Lecture_Py2.ipynb
│ │ │ └── Logical and Identity Operators - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Logical and Identity Operators - Exercise_Py3.ipynb
│ │ ├── Logical and Identity Operators - Lecture_Py3.ipynb
│ │ └── Logical and Identity Operators - Solution_Py3.ipynb
│ ├── S26_L155/
│ │ ├── Python 2/
│ │ │ ├── Introduction to the If Statement - Exercise_Py2.ipynb
│ │ │ ├── Introduction to the If Statement - Lecture_Py2.ipynb
│ │ │ └── Introduction to the If Statement - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Introduction to the If Statement - Exercise_Py3.ipynb
│ │ ├── Introduction to the If Statement - Lecture_Py3.ipynb
│ │ └── Introduction to the If Statement - Solution_Py3.ipynb
│ ├── S26_L156/
│ │ ├── Python 2/
│ │ │ ├── Add an Else Statement - Exercise_Py2.ipynb
│ │ │ ├── Add an Else Statement - Lecture_Py2.ipynb
│ │ │ └── Add an Else Statement - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Add an Else Statement - Exercise_Py3.ipynb
│ │ ├── Add an Else Statement - Lecture_Py3.ipynb
│ │ └── Add an Else Statement - Solution_Py3.ipynb
│ ├── S26_L157/
│ │ ├── Python 2/
│ │ │ ├── Else If, for Brief - Elif - Exercise_Py2.ipynb
│ │ │ ├── Else If, for Brief - Elif - Lecture_Py2.ipynb
│ │ │ └── Else If, for Brief - Elif - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Else If, for Brief - Elif - Exercise_Py3.ipynb
│ │ ├── Else If, for Brief - Elif - Lecture_Py3.ipynb
│ │ └── Else If, for Brief - Elif - Solution_Py3.ipynb
│ ├── S26_L158/
│ │ ├── Python 2/
│ │ │ └── A Note on Boolean Values - Lecture_Py2.ipynb
│ │ └── Python 3/
│ │ └── A Note on Boolean Values - Lecture_Py3.ipynb
│ ├── S27_L159/
│ │ ├── Python 2/
│ │ │ └── Defining a Function in Python - Lecture_Py2.ipynb
│ │ └── Python 3/
│ │ └── Defining a Function in Python - Lecture_Py3.ipynb
│ ├── S27_L160/
│ │ ├── Python 2/
│ │ │ ├── Creating a Function with a Parameter - Exercise_Py2.ipynb
│ │ │ ├── Creating a Function with a Parameter - Lecture_Py2.ipynb
│ │ │ └── Creating a Function with a Parameter - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Creating a Function with a Parameter - Exercise_Py3.ipynb
│ │ ├── Creating a Function with a Parameter - Lecture_Py3.ipynb
│ │ └── Creating a Function with a Parameter - Solution_Py3.ipynb
│ ├── S27_L161/
│ │ ├── Python 2/
│ │ │ ├── Another Way to Define a Function - Exercise_Py2.ipynb
│ │ │ ├── Another Way to Define a Function - Lecture_Py2.ipynb
│ │ │ └── Another Way to Define a Function - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Another Way to Define a Function - Exercise_Py3.ipynb
│ │ ├── Another Way to Define a Function - Lecture_Py3.ipynb
│ │ └── Another Way to Define a Function - Solution_Py3.ipynb
│ ├── S27_L162/
│ │ ├── Python 2/
│ │ │ ├── 0.6.4 Using a Function in another Function - Exercise_Py2.ipynb
│ │ │ ├── 0.6.4 Using a Function in another Function - Lecture_Py2.ipynb
│ │ │ └── 0.6.4 Using a Function in another Function - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── 0.6.4 Using a Function in another Function - Exercise_Py3.ipynb
│ │ ├── 0.6.4 Using a Function in another Function - Lecture_Py3.ipynb
│ │ └── 0.6.4 Using a Function in another Function - Solution_Py3.ipynb
│ ├── S27_L163/
│ │ ├── Python 2/
│ │ │ ├── Combining Conditional Statements and Functions - Exercise_Py2.ipynb
│ │ │ ├── Combining Conditional Statements and Functions - Lecture_Py2.ipynb
│ │ │ └── Combining Conditional Statements and Functions - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Combining Conditional Statements and Functions - Exercise_Py3.ipynb
│ │ ├── Combining Conditional Statements and Functions - Lecture_Py3.ipynb
│ │ └── Combining Conditional Statements and Functions - Solution_Py3.ipynb
│ ├── S27_L164/
│ │ ├── Python 2/
│ │ │ └── Creating Functions Containing a Few Arguments - Lecture_Py2.ipynb
│ │ └── Python 3/
│ │ └── Creating Functions Containing a Few Arguments - Lecture_Py3.ipynb
│ ├── S27_L165/
│ │ ├── Python 2/
│ │ │ ├── Notable Built-In Functions in Python - Exercise_Py2.ipynb
│ │ │ ├── Notable Built-In Functions in Python - Lecture_Py2.ipynb
│ │ │ └── Notable Built-In Functions in Python - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Notable Built-In Functions in Python - Exercise_Py3.ipynb
│ │ ├── Notable Built-In Functions in Python - Lecture_Py3.ipynb
│ │ └── Notable Built-In Functions in Python - Solution_Py3.ipynb
│ ├── S28_L166/
│ │ ├── Python 2/
│ │ │ ├── Lists - Exercise_Py2.ipynb
│ │ │ ├── Lists - Lecture_Py2.ipynb
│ │ │ └── Lists - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Lists - Exercise_Py3.ipynb
│ │ ├── Lists - Lecture_Py3.ipynb
│ │ └── Lists - Solution_Py3.ipynb
│ ├── S28_L167/
│ │ ├── Python 2/
│ │ │ ├── Help Yourself with Methods - Exercise_Py2.ipynb
│ │ │ ├── Help Yourself with Methods - Lecture_Py2.ipynb
│ │ │ └── Help Yourself with Methods - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Help Yourself with Methods - Exercise_Py3.ipynb
│ │ ├── Help Yourself with Methods - Lecture_Py3.ipynb
│ │ └── Help Yourself with Methods - Solution_Py3.ipynb
│ ├── S28_L168/
│ │ ├── Python 2/
│ │ │ ├── List Slicing - Exercise_Py2.ipynb
│ │ │ ├── List Slicing - Lecture_Py2.ipynb
│ │ │ └── List Slicing - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── List Slicing - Exercise_Py3.ipynb
│ │ ├── List Slicing - Lecture_Py3.ipynb
│ │ └── List Slicing - Solution_Py3.ipynb
│ ├── S28_L169/
│ │ ├── Python 2/
│ │ │ ├── Tuples - Exercise_Py2.ipynb
│ │ │ ├── Tuples - Lecture_Py2.ipynb
│ │ │ └── Tuples - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Tuples - Exercise_Py3.ipynb
│ │ ├── Tuples - Lecture_Py3.ipynb
│ │ └── Tuples - Solution_Py3.ipynb
│ ├── S28_L170/
│ │ ├── Python 2/
│ │ │ ├── Dictionaries - Exercise_Py2.ipynb
│ │ │ ├── Dictionaries - Lecture_Py2.ipynb
│ │ │ └── Dictionaries - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Dictionaries - Exercise_Py3.ipynb
│ │ ├── Dictionaries - Lecture_Py3.ipynb
│ │ └── Dictionaries - Solution_Py3.ipynb
│ ├── S29_L171/
│ │ ├── Python 2/
│ │ │ ├── For Loops - Exercise_Py2.ipynb
│ │ │ ├── For Loops - Lecture_Py2.ipynb
│ │ │ └── For Loops - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── For Loops - Exercise_Py3.ipynb
│ │ ├── For Loops - Lecture_Py3.ipynb
│ │ └── For Loops - Solution_Py3.ipynb
│ ├── S29_L172/
│ │ ├── Python 2/
│ │ │ ├── While Loops and Incrementing - Exercise_Py2.ipynb
│ │ │ ├── While Loops and Incrementing - Lecture_Py2.ipynb
│ │ │ └── While Loops and Incrementing - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── While Loops and Incrementing - Exercise_Py3.ipynb
│ │ ├── While Loops and Incrementing - Lecture_Py3.ipynb
│ │ └── While Loops and Incrementing - Solution_Py3.ipynb
│ ├── S29_L173/
│ │ ├── Python 2/
│ │ │ ├── Create Lists with the range() Function - Exercise_Py2.ipynb
│ │ │ ├── Create Lists with the range() Function - Lecture_Py2.ipynb
│ │ │ └── Create Lists with the range() Function - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Create Lists with the range() Function - Exercise_Py3.ipynb
│ │ ├── Create Lists with the range() Function - Lecture_Py3.ipynb
│ │ └── Create Lists with the range() Function - Solution_Py3.ipynb
│ ├── S29_L174/
│ │ ├── Python 2/
│ │ │ ├── Use Conditional Statements and Loops Together - Exercise_Py2.ipynb
│ │ │ ├── Use Conditional Statements and Loops Together - Lecture_Py2.ipynb
│ │ │ └── Use Conditional Statements and Loops Together - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── Use Conditional Statements and Loops Together - Exercise_Py3.ipynb
│ │ ├── Use Conditional Statements and Loops Together - Lecture_Py3.ipynb
│ │ └── Use Conditional Statements and Loops Together - Solution_Py3.ipynb
│ ├── S29_L175/
│ │ ├── Python 2/
│ │ │ ├── All In - Exercise_Py2.ipynb
│ │ │ ├── All In - Lecture_Py2.ipynb
│ │ │ └── All In - Solution_Py2.ipynb
│ │ └── Python 3/
│ │ ├── All In - Exercise_Py3.ipynb
│ │ ├── All In - Lecture_Py3.ipynb
│ │ └── All In - Solution_Py3.ipynb
│ └── S29_L176/
│ ├── Python 2/
│ │ ├── Iterating over Dictionaries - Exercise_Py2.ipynb
│ │ ├── Iterating over Dictionaries - Lecture_Py2.ipynb
│ │ └── Iterating over Dictionaries - Solution_Py2.ipynb
│ └── Python 3/
│ ├── Iterating over Dictionaries - Exercise_Py3.ipynb
│ ├── Iterating over Dictionaries - Lecture_Py3.ipynb
│ └── Iterating over Dictionaries - Solution_Py3.ipynb
├── Part_5_Advanced_Statistical_Methods_(Machine_Learning)/
│ ├── S32_L186/
│ │ ├── 1.01. Simple linear regression.csv
│ │ ├── Simple linear regression.ipynb
│ │ └── Simple linear regression_with_comments.ipynb
│ ├── S32_L187/
│ │ ├── real_estate_price_size.csv
│ │ ├── Simple Linear Regression Exercise Solution.ipynb
│ │ └── Simple Linear Regression Exercise.ipynb
│ ├── S33_L194/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── Multiple linear regression and Adjusted R-squared_.ipynb
│ │ └── Multiple linear regression and Adjusted R-squared_with_comments.ipynb
│ ├── S33_L195/
│ │ ├── Multiple Linear Regression Exercise Solution.ipynb
│ │ ├── Multiple Linear Regression Exercise.ipynb
│ │ └── real_estate_price_size_year.csv
│ ├── S33_L203/
│ │ ├── 1.03. Dummies.csv
│ │ ├── Dummy Variables.ipynb
│ │ └── Dummy variables_with_comments.ipynb
│ ├── S33_L204/
│ │ ├── Multiple Linear Regression with Dummies Exercise Solution.ipynb
│ │ ├── Multiple Linear Regression with Dummies Exercise.ipynb
│ │ └── real_estate_price_size_year_view.csv
│ ├── S33_L205/
│ │ ├── Making predictions.ipynb
│ │ └── Making predictions_with_comments.ipynb
│ ├── S34_L208/
│ │ ├── 1.01. Simple linear regression.csv
│ │ ├── sklearn - Simple Linear Regression.ipynb
│ │ └── sklearn - Simple Linear Regression_with_comments.ipynb
│ ├── S34_L209/
│ │ ├── 1.01. Simple linear regression.csv
│ │ ├── sklearn - Simple Linear Regression.ipynb
│ │ └── sklearn - Simple Linear Regression_with_comments.ipynb
│ ├── S34_L211/
│ │ ├── real_estate_price_size.csv
│ │ ├── Simple Linear Regression with sklearn - Exercise Solution.ipynb
│ │ └── Simple Linear Regression with sklearn - Exercise.ipynb
│ ├── S34_L212/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Multiple Linear Regression.ipynb
│ │ └── sklearn - Multiple Linear Regression_with_comments.ipynb
│ ├── S34_L213/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Multiple Linear Regression and Adjusted R-squared.ipynb
│ │ └── sklearn - Multiple Linear Regression and Adjusted R-squared_with_comments.ipynb
│ ├── S34_L214/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Multiple Linear Regression and Adjusted R-squared - Exercise Solution.ipynb
│ │ └── sklearn - Multiple Linear Regression and Adjusted R-squared - Exercise.ipynb
│ ├── S34_L215/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Feature Selection with F-regression.ipynb
│ │ └── sklearn - Feature Selection with F-regression_with_comments.ipynb
│ ├── S34_L216/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ └── sklearn - How to properly include p-values.ipynb
│ ├── S34_L217/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Multiple Linear Regression Summary Table.ipynb
│ │ └── sklearn - Multiple Linear Regression Summary Table_with_comments.ipynb
│ ├── S34_L218/
│ │ ├── real_estate_price_size_year.csv
│ │ ├── sklearn - Multiple Linear Regression Exercise Solution.ipynb
│ │ └── sklearn - Multiple Linear Regression Exercise.ipynb
│ ├── S34_L219/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Feature Selection through Feature Scaling (Standardization) - Part 1.ipynb
│ │ └── sklearn - Feature Selection through Feature Scaling (Standardization) - Part 1_with_comments.ipynb
│ ├── S34_L220/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Feature Selection through Feature Scaling (Standardization) - Part 2.ipynb
│ │ └── sklearn - Feature Selection through Feature Scaling (Standardization) - Part 2_with_comments.ipynb
│ ├── S34_L221/
│ │ ├── 1.02. Multiple linear regression.csv
│ │ ├── sklearn - Making Predictions with the Standardized Coefficients.ipynb
│ │ └── sklearn - Making Predictions with the Standardized Coefficients_with_comments.ipynb
│ ├── S34_L222/
│ │ ├── real_estate_price_size_year.csv
│ │ ├── sklearn - Feature Scaling Exercise Solution.ipynb
│ │ └── sklearn - Feature Scaling Exercise.ipynb
│ ├── S34_L224/
│ │ ├── sklearn - Train Test Split.ipynb
│ │ └── sklearn - Train Test Split_with_comments.ipynb
│ ├── S35_L225/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Linear Regression - Practical Example (Part 1).ipynb
│ │ └── sklearn - Linear Regression - Practical Example (Part 1)_with_comments.ipynb
│ ├── S35_L226/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Linear Regression - Practical Example (Part 2).ipynb
│ │ └── sklearn - Linear Regression - Practical Example (Part 2)_with_comments.ipynb
│ ├── S35_L228/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Linear Regression - Practical Example (Part 3).ipynb
│ │ └── sklearn - Linear Regression - Practical Example (Part 3)_with_comments.ipynb
│ ├── S35_L229/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Dummies and VIF - Exercise Solution.ipynb
│ │ └── sklearn - Dummies and VIF - Exercise.ipynb
│ ├── S35_L230/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Linear Regression - Practical Example (Part 4).ipynb
│ │ └── sklearn - Linear Regression - Practical Example (Part 4)_with_comments.ipynb
│ ├── S35_L232/
│ │ ├── 1.04. Real-life example.csv
│ │ ├── sklearn - Linear Regression - Practical Example (Part 5).ipynb
│ │ └── sklearn - Linear Regression - Practical Example (Part 5)_with_comments.ipynb
│ ├── S36_L235/
│ │ ├── 2.01. Admittance.csv
│ │ ├── Admittance.ipynb
│ │ └── Admittance_with_comments.ipynb
│ ├── S36_L237/
│ │ ├── Admittance regression tables_fixed_error.ipynb
│ │ ├── Admittance regression.ipynb
│ │ └── Admittance regression_summary_error.ipynb
│ ├── S36_L238/
│ │ ├── Building a Logistic Regression - Exercise.ipynb
│ │ ├── Building a Logistic Regression - Solution.ipynb
│ │ └── Example-bank-data.csv
│ ├── S36_L241/
│ │ ├── Bank-data.csv
│ │ ├── Understanding Logistic Regression Tables - Exercise.ipynb
│ │ └── Understanding Logistic Regression Tables - Solution.ipynb
│ ├── S36_L243/
│ │ ├── 2.02. Binary predictors.csv
│ │ └── Binary predictors.ipynb
│ ├── S36_L244/
│ │ ├── Bank-data.csv
│ │ ├── Binary Predictors in a Logistic Regression - Exercise.ipynb
│ │ └── Binary Predictors in a Logistic Regression - Solution.ipynb
│ ├── S36_L245/
│ │ ├── Accuracy.ipynb
│ │ └── Accuracy_with_comments.ipynb
│ ├── S36_L246/
│ │ ├── Bank-data.csv
│ │ ├── Calculating the Accuracy of the Model - Exercise.ipynb
│ │ └── Calculating the Accuracy of the Model - Solution.ipynb
│ ├── S36_L248/
│ │ ├── 2.03. Test dataset.csv
│ │ ├── Testing the model.ipynb
│ │ └── Testing the model_with_comments.ipynb
│ ├── S36_L249/
│ │ ├── Bank-data-testing.csv
│ │ ├── Bank-data.csv
│ │ ├── Testing the Model - Exercise..ipynb
│ │ └── Testing the Model - Solution.ipynb
│ ├── S38_L255/
│ │ ├── 3.01. Country clusters.csv
│ │ ├── Country clusters.ipynb
│ │ └── Country clusters_with_comments.ipynb
│ ├── S38_L256/
│ │ ├── A Simple Example of Clustering - Exercise.ipynb
│ │ ├── A Simple Example of Clustering - Solution.ipynb
│ │ └── Countries-exercise.csv
│ ├── S38_L257/
│ │ ├── Categorical data.ipynb
│ │ └── Categorical data_with_comments.ipynb
│ ├── S38_L258/
│ │ ├── Categorical.csv
│ │ ├── Clustering Categorical Data - Exercise.ipynb
│ │ └── Clustering Categorical Data - Solution.ipynb
│ ├── S38_L259/
│ │ ├── Selecting the number of clusters.ipynb
│ │ └── Selecting the number of clusters_with_comments.ipynb
│ ├── S38_L260/
│ │ ├── Countries-exercise.csv
│ │ ├── How to Choose the Number of Clusters - Exercise.ipynb
│ │ └── How to Choose the Number of Clusters - Solution.ipynb
│ ├── S38_L264/
│ │ ├── 3.12. Example.csv
│ │ ├── Market segmentation example.ipynb
│ │ └── Market segmentation example_with_comments.ipynb
│ ├── S38_L265/
│ │ ├── Market segmentation example_Part2.ipynb
│ │ └── Market segmentation example_Part2_with_comments.ipynb
│ ├── S38_L267/
│ │ ├── iris-dataset.csv
│ │ ├── Species Segmentation with Cluster Analysis Part 1- Exercise.ipynb
│ │ └── Species Segmentation with Cluster Analysis Part 1- Solution.ipynb
│ ├── S38_L268/
│ │ ├── iris-dataset.csv
│ │ ├── iris-with-answers.csv
│ │ ├── Species Segmentation with Cluster Analysis Part 2 - Exercise.ipynb
│ │ └── Species Segmentation with Cluster Analysis Part 2 - Solution.ipynb
│ └── S39_L271/
│ ├── Country clusters standardized.csv
│ ├── Heatmaps.ipynb
│ └── Heatmaps_with_comments.ipynb
├── Part_6_Mathematics/
│ ├── S40_L275/
│ │ └── Scalars, Vectors, and Matrices.ipynb
│ ├── S40_L276/
│ │ └── Tensors.ipynb
│ ├── S40_L277/
│ │ └── Adding and subtracting matrices.ipynb
│ ├── S40_L278/
│ │ └── Errors when adding scalars, vectors, and matrices in Python.ipynb
│ ├── S40_L279/
│ │ └── Tranpose of a matrix.ipynb
│ ├── S40_L280/
│ │ └── Dot product.ipynb
│ └── S40_L281/
│ └── Dot product (Part 2).ipynb
├── Part_7_Deep_Learning/
│ ├── S43_L296/
│ │ └── Minimal_example_Part_1.ipynb
│ ├── S43_L297/
│ │ └── Minimal_example_Part_2.ipynb
│ ├── S43_L298/
│ │ └── Minimal_example_Part_3.ipynb
│ ├── S43_L299/
│ │ └── Minimal_example_Part_4_Complete.ipynb
│ ├── S43_L300/
│ │ ├── Minimal_example_All_Exercises.ipynb
│ │ ├── Minimal_example_Exercise_1_Solution.ipynb
│ │ ├── Minimal_example_Exercise_2_Solution.ipynb
│ │ ├── Minimal_example_Exercise_3.a. Solution.ipynb
│ │ ├── Minimal_example_Exercise_3.b. Solution.ipynb
│ │ ├── Minimal_example_Exercise_3.c. Solution.ipynb
│ │ ├── Minimal_example_Exercise_3.d. Solution.ipynb
│ │ ├── Minimal_example_Exercise_4_Solution.ipynb
│ │ ├── Minimal_example_Exercise_5_Solution.ipynb
│ │ ├── Minimal_example_Exercise_6.ipynb
│ │ └── Minimal_example_Exercise_6_Solution.ipynb
│ ├── S44_L304/
│ │ └── Shortcuts-for-Jupyter.pdf
│ ├── S44_L305/
│ │ └── TensorFlow_Minimal_example_Part1.ipynb
│ ├── S44_L306/
│ │ └── TensorFlow_Minimal_example_Part2.ipynb
│ ├── S44_L307/
│ │ └── TensorFlow_Minimal_example_Part3.ipynb
│ ├── S44_L308/
│ │ ├── TensorFlow_Minimal_example_complete.ipynb
│ │ └── TensorFlow_Minimal_example_complete_with_comments.ipynb
│ ├── S44_L309/
│ │ ├── TensorFlow_Minimal_example_All_exercises.ipynb
│ │ ├── TensorFlow_Minimal_example_Exercise_1_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_1_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_2_Solution.ipynb
│ │ └── TensorFlow_Minimal_Example_Exercise_3_Solution.ipynb
│ ├── S45_L310/
│ │ └── Course-Notes-Section-6.pdf
│ ├── S45_L311/
│ │ └── Course-Notes-Section-6.pdf
│ ├── S45_L318/
│ │ └── Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf
│ ├── S50_L340/
│ ├── S50_L341/
│ ├── S50_L342/
│ │ └── TensorFlow_MNIST_Part1_with_comments.ipynb
│ ├── S50_L344/
│ │ └── TensorFlow_MNIST_Part2_with_comments.ipynb
│ ├── S50_L346/
│ │ └── TensorFlow_MNIST_Part3_with_comments.ipynb
│ ├── S50_L347/
│ │ └── TensorFlow_MNIST_Part4_with_comments.ipynb
│ ├── S50_L348/
│ │ └── TensorFlow_MNIST_Part5_with_comments.ipynb
│ ├── S50_L349/
│ │ └── TensorFlow_MNIST_Part6_with_comments.ipynb
│ ├── S50_L350/
│ │ ├── 1. TensorFlow_MNIST_Width_Solution.ipynb
│ │ ├── 2. TensorFlow_MNIST_Depth_Solution.ipynb
│ │ ├── 3. TensorFlow_MNIST_Width_and_Depth_Solution.ipynb
│ │ ├── 4. TensorFlow_MNIST_Activation_functions_Part_1_Solution.ipynb
│ │ ├── 5. TensorFlow_MNIST_Activation_functions_Part_2_Solution.ipynb
│ │ ├── 6. TensorFlow_MNIST_Batch_size_Part_1_Solution.ipynb
│ │ ├── 7. TensorFlow_MNIST_Batch_size_Part_2_Solution.ipynb
│ │ ├── 8. TensorFlow_MNIST_Learning_rate_Part_1_Solution.ipynb
│ │ ├── 9. TensorFlow_MNIST_Learning_rate_Part_2_Solution.ipynb
│ │ ├── TensorFlow_MNIST_All_Exercises.ipynb
│ │ └── TensorFlow_MNIST_around_98_percent_accuracy.ipynb
│ ├── S50_L351/
│ │ ├── TensorFlow_MNIST_complete.ipynb
│ │ └── TensorFlow_MNIST_complete_with_comments.ipynb
│ ├── S51_L352/
│ │ └── Audiobooks_data.csv
│ ├── S51_L355/
│ │ ├── Audiobooks_data.csv
│ │ ├── TensorFlow_Audiobooks_Preprocessing.ipynb
│ │ └── TensorFlow_Audiobooks_Preprocessing_with_comments.ipynb
│ ├── S51_L356/
│ │ ├── Audiobooks_data.csv
│ │ ├── TensorFlow_Audiobooks_Preprocessing_Exercise.ipynb
│ │ └── TensorFlow_Audiobooks_Preprocessing_Exercise_Solution.ipynb
│ ├── S51_L358/
│ │ └── TensorFlow_Audiobooks_Machine_Learning_Part1_with_comments.ipynb
│ ├── S51_L359/
│ │ └── TensorFlow_Audiobooks_Machine_Learning_Part2_with_comments.ipynb
│ ├── S51_L360/
│ │ └── TensorFlow_Audiobooks_Machine_Learning_Part3_with_comments.ipynb
│ ├── S51_L362/
│ │ └── TensorFlow_Audiobooks_Machine_Learning_with_comments.ipynb
│ ├── S51_L363/
│ │ └── TensorFlow_Audiobooks_Machine_Learning_with_comments.ipynb
│ ├── S53_L374/
│ │ └── Shortcuts-for-Jupyter.pdf
│ ├── S53_L375/
│ │ └── 5.3. TensorFlow_Minimal_example_Part_1.ipynb
│ ├── S53_L376/
│ │ └── 5.4. TensorFlow_Minimal_example_Part_2.ipynb
│ ├── S53_L377/
│ │ └── 5.5. TensorFlow_Minimal_example_Part_3.ipynb
│ ├── S53_L378/
│ │ └── 5.6. TensorFlow_Minimal_example_complete.ipynb
│ ├── S53_L379/
│ │ ├── TensorFlow_Minimal_Example_All_Exercises.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_1_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_1_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_2_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_3_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_2_4_Solution.ipynb
│ │ ├── TensorFlow_Minimal_Example_Exercise_3_Solution.ipynb
│ │ └── TensorFlow_Minimal_Example_Exercise_4_Solution.ipynb
│ ├── S54_L382/
│ │ └── 12.3. TensorFlow_MNIST_with_comments_Part_1.ipynb
│ ├── S54_L383/
│ │ └── 12.4. TensorFlow_MNIST_with_comments_Part_2.ipynb
│ ├── S54_L384/
│ │ └── 12.5. TensorFlow_MNIST_with_comments_Part_3.ipynb
│ ├── S54_L385/
│ │ └── 12.6. TensorFlow_MNIST_with_comments_Part_4.ipynb
│ ├── S54_L386/
│ │ └── 12.7. TensorFlow_MNIST_with_comments_Part_5.ipynb
│ ├── S54_L387/
│ │ └── 12.8. TensorFlow_MNIST_with_comments_Part_6.ipynb
│ ├── S54_L388/
│ │ └── 12.9. TensorFlow_MNIST_with_comments.ipynb
│ ├── S54_L389/
│ │ └── TensorFlow_MNIST_Exercises_All.ipynb
│ ├── S54_L390/
│ │ ├── 0. TensorFlow_MNIST_take_note_of_time_Solution.ipynb
│ │ ├── 1. TensorFlow_MNIST_Width_Solution.ipynb
│ │ ├── 2. TensorFlow_MNIST_Depth_Solution.ipynb
│ │ ├── 3. TensorFlow_MNIST_Width_and_Depth_Solution.ipynb
│ │ ├── 4. TensorFlow_MNIST_Activation_functions_Part_1_Solution.ipynb
│ │ ├── 5. TensorFlow_MNIST_Activation_functions_Part_2_Solution.ipynb
│ │ ├── 6. TensorFlow_MNIST_Batch_size_Part_1_Solution.ipynb
│ │ ├── 7. TensorFlow_MNIST_Batch_size_Part_2_Solution.ipynb
│ │ ├── 8. TensorFlow_MNIST_Learning_rate_Part_1_Solution.ipynb
│ │ ├── 9. TensorFlow_MNIST_Learning_rate_Part_2_Solution.ipynb
│ │ └── TensorFlow_MNIST_around_98_percent_accuracy.ipynb
│ ├── S55_L391/
│ │ └── Audiobooks-data.csv
│ ├── S55_L392/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── TensorFlow_Audiobooks_Preprocessing_lesson-checkpoint.ipynb
│ │ │ └── TensorFlow_Audiobooks_Preprocessing_with_comments-checkpoint.ipynb
│ │ ├── Audiobooks_data.csv
│ │ ├── TensorFlow_Audiobooks_Preprocessing.ipynb
│ │ └── TensorFlow_Audiobooks_Preprocessing_with_comments.ipynb
│ ├── S55_L394/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── TensorFlow_Audiobooks_Batching-checkpoint.ipynb
│ │ └── TensorFlow_Audiobooks_Batching.ipynb
│ ├── S55_L395/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── TensorFlow_Audiobooks_Preprocessing_Exercise-checkpoint.ipynb
│ │ │ └── TensorFlow_Audiobooks_Preprocessing_Exercise_Solution-checkpoint.ipynb
│ │ ├── Audiobooks_data.csv
│ │ ├── TensorFlow_Audiobooks_Preprocessing_Exercise.ipynb
│ │ └── TensorFlow_Audiobooks_Preprocessing_Exercise_Solution.ipynb
│ ├── S55_L397/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── TensorFlow_Audiobooks_Outlining_the_model-checkpoint.ipynb
│ │ │ └── TensorFlow_Audiobooks_Outlining_the_model_with_comments-checkpoint.ipynb
│ │ ├── TensorFlow_Audiobooks_Outlining_the_model.ipynb
│ │ └── TensorFlow_Audiobooks_Outlining_the_model_with_comments.ipynb
│ ├── S55_L398/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── TensorFlow_Audiobooks_optimizing_the_algorithm-checkpoint.ipynb
│ │ │ └── TensorFlow_Audiobooks_optimizing_the_algorithm_with_comments-checkpoint.ipynb
│ │ ├── TensorFlow_Audiobooks_optimizing_the_algorithm.ipynb
│ │ └── TensorFlow_Audiobooks_optimizing_the_algorithm_with_comments.ipynb
│ ├── S55_L399/
│ │ ├── TensorFlow_Audiobooks_optimizing_the_algorithm.ipynb
│ │ └── TensorFlow_Audiobooks_optimizing_the_algorithm_with_comments.ipynb
│ ├── S55_L400/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── TensorFlow_Audiobooks_Machine_learning_with_comments-checkpoint.ipynb
│ │ ├── Audiobooks_data.csv
│ │ ├── TensorFlow_Audiobooks_Machine_learning_Homework.ipynb
│ │ └── TensorFlow_Audiobooks_Preprocessing_with_comments.ipynb
│ └── S55_L402/
│ ├── .ipynb_checkpoints/
│ │ └── TensorFlow_Audiobooks_Machine_learning_with_comments-checkpoint.ipynb
│ ├── Audiobooks_data.csv
│ ├── TensorFlow_Audiobooks_Machine_learning_Homework.ipynb
│ └── TensorFlow_Audiobooks_Preprocessing_with_comments.ipynb
├── Part_8_Case_Study/
│ ├── S58_L411/
│ │ ├── Absenteeism-data.csv
│ │ ├── data-preprocessing-homework.pdf
│ │ └── df-preprocessed.csv
│ ├── S58_L433/
│ ├── S58_L439/
│ │ └── Absenteeism Exercise - Removing the Date Column - SOLUTION.ipynb
│ ├── S58_L442/
│ │ ├── Absenteeism Exercise - EXERCISES and SOLUTIONS.ipynb
│ │ └── Absenteeism Exercise - Preprocessing.ipynb
│ ├── S59_L443/
│ │ └── Absenteeism-preprocessed.csv
│ ├── S59_L452/
│ │ └── Absenteeism Exercise - Logistic Regression_prior to custom_scaler.ipynb
│ ├── S59_L454/
│ │ └── Absenteeism Exercise - Logistic Regression_prior_to_backward_elimination.ipynb
│ ├── S59_L458/
│ │ ├── Absenteeism Exercise - Logistic Regression.ipynb
│ │ └── Absenteeism Exercise - Logistic Regression_with_comments.ipynb
│ ├── S60_L460/
│ │ ├── Absenteeism Exercise - Integration.ipynb
│ │ ├── absenteeism_module.py
│ │ ├── Absenteeism_new_data.csv
│ │ ├── model
│ │ └── scaler
│ ├── S60_L463/
│ │ └── Absenteeism Exercise - Deploying the 'absenteeism_module'.ipynb
│ └── S60_L464/
│ ├── Absenteeism Exercise - Deploying the 'absenteeism_module'.ipynb
│ └── Absenteeism_predictions.csv
├── Part_9_Appendix/
│ ├── Additional-Python-Tools-Exercises.ipynb
│ ├── Additional-Python-Tools-Lectures.ipynb
│ └── Additional-Python-Tools-Solutions.ipynb
└── README.md