This repository archives materials for an online Machine Learning course by Coding Blocks, targeting individuals seeking a comprehensive understanding of ML concepts from Python basics to advanced deep learning and reinforcement learning. It offers over 200 video tutorials and 15 projects, aiming to equip students with practical skills for building intelligent systems.

How It Works

The course progresses from Python fundamentals and data visualization to supervised and unsupervised learning algorithms. It then delves into deep learning, covering neural networks, CNNs for computer vision, and RNNs/LSTMs for NLP, concluding with reinforcement learning. The curriculum emphasizes building solutions from scratch while also introducing key libraries like Pandas, NumPy, Matplotlib, Sci-kit Learn, Keras, TensorFlow, and OpenAI Gym.

Quick Start & Requirements

• Prerequisites: Familiarity with any programming language (Python preferred), data structures, OOP concepts, and Git/GitHub.
• Libraries: Pandas, Matplotlib, NumPy, Keras, TensorFlow, Sci-kit Learn, OpenAI Gym.
• Resources: Access to course videos on online.codingblocks.com.

Highlighted Details

• Comprehensive curriculum covering 7 major categories of ML and Deep Learning.
• Hands-on experience with 20 mini-projects and a final Image Captioning project.
• Focus on building algorithms from scratch alongside library usage.
• Taught by an instructor with an MS in Deep Learning from IIT Delhi.

Maintenance & Community

• The repository appears to be a static archive of course materials from 2018. No active maintenance or community channels are indicated.

Licensing & Compatibility

• The repository does not explicitly state a license.

Limitations & Caveats

• The course materials are from 2018, meaning the content, libraries, and best practices may be outdated. There is no indication of ongoing support or updates.