Deep Learning with TensorFlow & Keras 

Course Overview


Our Deep Learning Course will give you all the knowledge needed to work on Deep Learning libraries like Keras and Tensorflow. In this training you we will learn about what AI, ML, explore neural networks, understand deep learning frameworks, and implement various machine learning algorithms using Deep Networks. We will also explore how different layers in neural networks do data abstraction and feature extraction using Deep Learning.

Expectations and Goals

Deep Learning and TensorFlow Concepts
Using Python with TensorFlow Libraries
Working with Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Working with Keras
Implementing Restricted Boltz-mann Machine (RBM)

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Course Duration :

32 Hours (16 days, 2 hours each day)

Trainer Experience :

25 Years in Corporate Training


Anybody interested in Deep Learning can take this Training. Though knowledge of 
following will be a plus point:
   Python programming
   Machine Learning

Course Schedule Module Topic

Module 1
    Why Deep Learning?
    What is a neural network?
    Reasons to go Deep
    Choice of Deep Net

Module 2
    Introduction to Artificial Neural Networks
    Feedforward Neural networks
    Activation functions

Module 3
    Introduction to python
    Python data types

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Module 4
    Introduction to Numpy
    Creating N-Dimensional numpy arrays
    Array mathematics
    Slicing N-Dimensional array
    Introduction to pandas
    Working with pandasSeries
    Working with pandas Dataframe

Module 5
    Restricted Boltzmann Machines
    Deep Belief Nets
    Convolutional Networks
    Recurrent Nets

Module 6
    Recursive Neural Tensor Nets

Module 7 
    Introduction to TensorFlow
    HelloWorld with TensorFlow
    Basic computation with TensorFlow

Module 8

    Introduction to Keras
    Keras vs TensorFlow
    Building Basic models with Keras

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Module 9
    CNN History
    Understanding CNNs
    CNN Application using Keras

Module 10
    Intro to RNN Model
    Long Short-Term memory (LSTM)
    Recursive Neural Tensor Network Theory
    Applications of Unsupervised Learning
    Restricted Boltzmann Machine   

Module 11

    Project work and documentation

Thank You

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