/Machine-Learning-Make-computers-think

Repository for all the resources used in the course Machine learning: making computers think on udemy

Primary LanguageJupyter Notebook

Machine Learning: Making computers think

This Repo consists of the notebook used in this course, course structure and other resources that can be useful in getting deeper intuition about the concepts of machine learning.

Course Directory:

├── 01-Introduction
|   |---1. about me
│   ├── 2. intro
│   ├── 3. SupVsUnsup
│   ├── 4. Setup environment
│   ├── 5. installing dep
│   └── 6. Setup up jupyter
├── 02-Data Collection
│   ├── 1. DataFetch
│   └── 2. DataImport
├── 03-Data Analysis
│   ├── 1. Introduction
│   ├── 2. Data exploration
│   ├── 3. Numericalvscat
│   ├── 4. Descriptive and Inferential stats
│   ├── 5. Data Visulalization
│   └── 6. Handling outlier
├── 04-Preprocessing
│   ├── 1. Introduction
│   ├── 2. Standarization and Normalization
│   ├── 3. Processing Categorical Data
│   └── 4. Handling Missing Values
├── 05-Data Modelling
│   ├── 1. Introduction
│   ├── 2. Types of ML Algorithm
│   ├── 3. Data Modelling
│   └── 4. Feature Selection
├── 06-Model Validation
│   ├── 1. Introduction
│   ├── 2. Metrics for validation
│   ├── 3. Trying different Metrics
│   ├── 4. Miscellanious Methods For Validation
│   ├── 5. Overfit vs Underfit
│   ├── 6. Methods to improve accuracy
│   └── 7. Hyperparameter Tuning
├── 07-Ensemble Learning
│   ├── 1. Introduction
│   ├── 2. Why ensembling
│   ├── 3. Different Ensembling Techniques
│   └── 4. Applying Ensembling
├── 08-Dimensionality Reduction
│   ├── 1. Introduction
│   ├── 2. Curse of Dimensionality
│   └── 3. Principal Component Analysis
└── 09-Outro

Reading Resources

These are the list of top trending blogs for machine learning and AI. Follow them on most recent trends and research in this advancing field.

Video Resources

Below Mentioned are some TED talks given on the topic of Machine learning in recent years. Try to watch them to get a more insightful knowledge about Machine Learning.

  • Anthony Goldbloom: The jobs we'll lose to machines — and the ones we won't Link to Video
  • Blaise Agüera y Arcas: How computers are learning to be creative Link to Video

References