Machine Learning

Dive into a comprehensive 60-hour machine learning course covering a wide range of topics from neural networks to deep learning. Learn to implement TensorFlow 2.0, Keras, PyTorch, and OpenCV in Python for various applications. Explore natural language processing, reinforcement learning, and JavaScript-based neural networks. Develop practical skills through hands-on projects like creating an AI for Connect Four and beating Asteroids using neural networks. Gain a solid theoretical foundation in neural networks and deep learning, and apply your knowledge to real-world data analysis and machine learning tasks using popular libraries like Scikit-learn.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial.
Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard.
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial.
OpenCV Course - Full Tutorial with Python.
How Deep Neural Networks Work - Full Course for Beginners.
Deep Learning Crash Course for Beginners.
Applied Deep Learning with PyTorch - Full Course.
Learn TensorFlow.js - Deep Learning and Neural Networks with JavaScript.
Natural Language Processing (NLP) Tutorial with Python & NLTK.
Reinforcement Learning Course - Full Machine Learning Tutorial.
TensorFlow 2.0 Crash Course.
Neural Networks with JavaScript - Full Course using Brain.js.
Develop an AI to play Connect Four - Python Tutorial.
Natural Language Processing with TensorFlow 2 - Beginner's Course.
Theory of Neural Networks - Deep Learning Without Frameworks.
Deep Reinforcement Learning in Python Tutorial - A Course on How to Implement Deep Learning Papers.
Beat Asteroids Game Using a Neural Network - JavaScript Tutorial.
Data Analysis with Python: Part 1 of 6 (Live Course).
Scikit-learn Crash Course - Machine Learning Library for Python.
Scikit-Learn Course - Machine Learning in Python Tutorial.