Build drowsiness detection system, predict energy consumption, forecast weather with CNN, RNN, GRU, Keras, Tensorflow
What you will learn
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Learn the basic fundamentals of deep learning, reinforcement learning, neural networks, and also getting to know their use cases
Learn how to build drowsiness detection model using Convolutional Neural Networks and Keras
Learn how to build drowsiness detection system using OpenCV
Learn how to build traffic light colour detection model using Convolutional Neural Networks and Keras
Learn how to build traffic light colour detection system using OpenCV
Learn how to build maze solver using reinforcement learning
Learn how to create maze using Pygame
Learn how to build smart traffic light system using reinforcement learning
Learn how to create traffic light simulation using Pygame
Learn how to predict energy consumption using Multilayer Perceptron Regression
Learn how to forecast weather using recurrent neural networks and gated recurrent unit
Learn how to build handwritten digit recognition using artificial neural networks
Learn how deep learning models work. This section covers input data, forward propagation, prediction output, loss calculation, backpropagation, and optimization
Learn how reinforcement learning models work. This section covers environment observation, action selection, reward, penalty, policy update, continuous learning
Learn how neural network models work. This section covers how input data flows through weighted connections and hidden layers
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