Learn Python, NumPy, Pandas, Matplotlib, PyTorch, and Linear Algebra—the foundations for building your own neural network.
Code:
Part 01-Module 01-Lesson 01_Welcome to AI Programming with Python
Part 02-Module 01-Lesson 01_Why Python Programming
Part 02-Module 01-Lesson 02_Data Types and Operators
Part 02-Module 01-Lesson 03_Control Flow
Part 02-Module 01-Lesson 04_Functions
Part 02-Module 01-Lesson 05_Scripting
Part 02-Module 02-Lesson 01_Lab Classifying Images
Part 03-Module 01-Lesson 01_Anaconda
Part 03-Module 01-Lesson 02_Jupyter Notebooks
Part 03-Module 01-Lesson 03_NumPy
Part 03-Module 01-Lesson 04_Pandas
Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1
Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2
Part 04-Module 01-Lesson 01_Introduction
Part 04-Module 01-Lesson 02_Vectors
Part 04-Module 01-Lesson 03_Linear Combination
Part 04-Module 01-Lesson 04_Linear Transformation and Matrices
Part 04-Module 02-Lesson 01_Vectors Lab
Part 04-Module 02-Lesson 02_Linear Combination Lab
Part 04-Module 02-Lesson 03_Linear Mapping Lab
Part 04-Module 02-Lesson 04_Linear Algebra in Neural Networks
Part 05-Module 01-Lesson 01_Introduction to Neural Networks
Part 05-Module 01-Lesson 02_Implementing Gradient Descent
Part 05-Module 01-Lesson 03_Training Neural Networks
Part 05-Module 01-Lesson 04_Deep Learning with PyTorch
Part 06-Module 01-Lesson 01_ Create Your Own Image Classifier
Part 07-Module 01-Lesson 01_How Do I Continue From Here
Part 08-Module 01-Lesson 01_What is Version Control
Part 08-Module 01-Lesson 02_Create A Git Repo
Part 08-Module 01-Lesson 03_Review a Repo's History
Part 08-Module 01-Lesson 04_Add Commits To A Repo
Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging
Part 08-Module 01-Lesson 06_Undoing Changes
Part 08-Module 02-Lesson 01_Working With Remotes
Part 08-Module 02-Lesson 02_Working On Another Developer's Repository
Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository
Part 09-Module 01-Lesson 01_Shell Workshop
Part 10-Module 01-Lesson 01_Intro
Part 10-Module 01-Lesson 02_Linear Regression
Part 10-Module 01-Lesson 03_Logistic Regression
Part 10-Module 01-Lesson 04_Decision Trees
Part 10-Module 01-Lesson 05_Naive Bayes
Part 10-Module 01-Lesson 06_Support Vector Machines
Part 10-Module 01-Lesson 07_Ensemble Methods
Part 10-Module 01-Lesson 08_Outro
Part 11-Module 01-Lesson 01_Visualizing The Importance Of The Learning Rate
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