Deep Learning with Python
Deep Learning with Python
Learning Outcomes
After attending the course, the participants:
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Will be able to demonstrate understanding of Deep Learning an its different variants.
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Identify the deep learning algorithms which are more appropriate for various types of learning tasks in various domains.
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Implement deep learning algorithms and solve real-world problems.
Details Plan:
Deep learning basics:
• Intro, History, capabilities, the perceptron • Activation Functions • Loss Functions • Gradient Descent, Back Propagation • Optimizers • Hyper Parameters • Different Types of Architectures .
Regression and Classification :
• Deep Learning Case Study with TensorFlow
Convolutional neural networks:
• Intro to CNNs, Convolution, Correlation, FIltering. • CNN architectures • Detection and Segmentation • Visualizing and Understanding • Advanced CNNs for computer vision
Representation Learning:
• Word Embedding • Auto Encoder
Recurrent Units :
• Recurrent Neural networks (RNNs) • Advanced RNN: LSTM, GRU,
Advanced Topics :
• Deep reinforcement learning • GAN
Pre-requisite:
● Basic Python Programming Knowledge
● Some exposure to Numpy, Pandas etc.
Duration
● 20 Hours