Collection of lectures and lab lectures on machine learning and deep learning.

• Gradient_Descent - slides on gradient descent optimization.
• Neural Networks and Deep Neural Networks - slides on neural networks and deep neural networks.
• Convolutional Neural Networks - slides on convolutional neural networks.
• Recurrent Neural Networks - slides on recurrent neural networks.

• Introduction and Model Free Learning - Introduction to reinforcement learning and model free learning.
• Function Approximation - Overview of function approximation methods

• Boosting
• Clustering
• Dimensionality Reduction
• Logistic Regression
• Naive Bayes
• Q Learning
• Support Vector Machine
• Introduction to TensorFlow
• Linear Regression (TensorFlow)
• Neural Networks (TensorFlow)
• Convolutional Networks (TensorFlow)
• Recurrent Networks (TensorFlow)