Deep Learning models are dominating nowadays in a variety of application domains and have outperformed the classical machine learning models in many ways. It is always a curiosity across the developers and learners on how to build efficient deep learning models for interesting applications.
In this workshop, developing deep learning models from scratch will be discussed through which the participants will learn how to start, develop and apply these models in real-life applications. These implementations will be done with Keras using the TensorFlow backend.
Pre-recorded videos (More than 7 hours of content) & colab notebooks
01. Introduction to Deep Learning: 5min
02. Deep Learning and Artificial Neural Networks: 82min
03. Deep Neural Network for Classification: 30Min
04. Convolutional Neural Networks: 85min
05. Convolutional Neural Network for Image Classification: 65min
06. Recurrent Neural Network and LSTM Model: 21min
07. Sequence Modeling: 25min
08. Autoencoders and Image Reconstruction: 32min
09. Generative Adversarial Network (GAN) for Fake Image Generation: 25min
10. Neural Style Transfer: 41min
11. Real-Time Object Detection in Images and Videos: 16min
+ 10 COLAB Notebooks