1. An Introduction to Machine Learning

  1. Introduction.srt

  2. What is Machine Learning.srt

  3. Types and Applications of ML.srt

  4. AI vs ML.srt

  5. Essential Math for ML and AI.srt

  6.1 Unit 1 Quiz.pdf.pdf

  7.1 Unit 1 Solutions.pdf.pdf

 10. Project 5 Object Recognition

  1. Intro.srt

  2. Loading and Preprocessing the CIFAR10 Dataset.mp4

  3. Building and Deploying the All-CNN Network Part 1.mp4

  4. Building and Deploying the All-CNN Network Part 2.mp4

 11. Project 6 Image Super Resolution

  1. Intro.srt

  2. Quality Metrics and Preprocessing Images.mp4

  3. Image Super Resolution using Deep Learning.mp4

 12. Project 7 Text Classification

  1. Intro.srt

  2. Feature Engineering.mp4

  3. Deploying Sklearn Classifiers.mp4

 13. Project 8 - KMeans

  1. Intro.srt

  2. Preprocessing Images for Clustering.mp4

  3. Evaluation and Visualization.mp4

 14. Project 9 PCA

  1. Intro.srt

  2. The Elbow Method.mp4

  3. PCA Compression and Visualization.mp4

 2. Supervised Learning - part 1

  1. Introduction to Supervised Learning.srt

  10.1 Unit 2 Solutions.pdf.pdf

  2. Linear Methods for Classification.srt

  3. Linear Methods for Regression.srt

  4. Support Vector Machines.srt

  5. Basis Expansions.srt

  6. Model Selection Procedures.srt

  7. Bonus! Supervised Learning Project in Python Part 1.srt

  8. Bonus! Supervised Learning Project in Python Part 2.mp4

  9. Quiz- Questions- Section 2.html

 3. Unsupervised Learning

  1. Introduction to Unsupervised Learning.srt

  2. Association Rules.srt

  3. Cluster Analysis.srt

  4. Reinforcement Learning.srt

  5. Bonus! KMeans Clustering Project.srt

  6. Quiz- Questions- Section 3.html

  7. Quiz- Answers - Section 3.html

 4. Neural Networks

  1. Introduction to Neural Networks.srt

  2. The Perceptron.srt

  3. The Backpropagation Algorithm.srt

  4. Training Procedures.srt

  5. Convolutional Neural Networks.srt

 5. Real World Machine Learning

  1. Introduction to Real World ML.srt

  2. Choosing an Algorithm.srt

  3. Design and Analysis of ML Experiments.srt

  4. Common Software for ML.srt

  5.1 Unit 5 Quiz.pdf.pdf

  6.1 Unit 5 Solutions.pdf.pdf

 6. Warmup Project

  1. Setting up OpenAI Gym.srt

  2. Building and Training the Network Part 1.mp4

  3. Building and Training the Network Part 2.mp4

 7. Project 1Board Game Review Prediction

  1. Intro.srt

  2. Board Game Review Prediction - Building the Dataset Part 1.mp4

  3. Board Game Review Prediction - Building the Dataset Part 2.mp4

  4. Board Game Review Prediction - Training the Models.mp4

 8. Project 2 Credit Card Fraud Detection

  1. Intro.srt

  2. Credit Card Fraud Detection - The Dataset.mp4

  3. Credit Card Fraud Detection - The Algorithms.mp4

 9. Project 4 Intro to Natural Language Processing

  1. Intro.srt

  2. Tokenizing, Stop Words, and Stemming.mp4

  3. Tagging, Chunking, and Named Entity Recognition.mp4

  4. Text Classification.mp4