Live Online Style Video +Live Instructor + Official Courseware + Hands-on Labs

TensorFlow

Includes:

  1. 6 months access to videos.
  2. Access via Laptop, Tab, Mobile, and Smart TV.
  3. Certificate of Completion.
  4. Hands-on labs
  5. 80+ Tests Questions (Qubits42)

We do not have video for this course. It will take 5 days to deliver.

You can also purchase an annual plan for USD 999. For one year, all Flexi Videos will be free for you. Buy Annual Plan

Flexi Video

USD 99

Official Courseware

N/A

Hands-On-Labs

USD 59

Total

USD 99

100% Refund for Flexi Video (courseware is non-refundable) if user is not satisfied with the Video and seeks refund within 30 days of purchase.

Download Course Contents
Module 1: Introduction
  • Introduction to TensorFlow
  • Architecture of Tensorflow
  • Installation on Local Machine
  • Using TensorFlow in Google Colab
  • Working with Tensors and Operations
  • Keras Low level api
  • From Biological to Artificial Neurons
  • Different activation functions
  • What is perceptron?
  • Multilayer perceptron and back propagation
  • Working with sequential api
  • Working with the functional api
  • Using callbacks
  • Tensorboard for visualization
  • Challenges of Deep Neural Network
  • Vanishing and Exploding gradients
  • Glorot and He Initialization
  • Non Saturating Activation Functions
  • Different activation functions effect on deep neural nets
  • Batch normalization
  • Reusing the pre-trained layers in Neural nets
  • Faster optimizers
  • L1 and L2 regularization
  • Dropouts and their purposes
  • The data api
  • Chaining transformations
  • Pre-processing the data
  • TFR record format and compressed files
  • Introduction to protocol buffer
  • Processing the Input features
  • TF transform
  • Tensorflow datasets project
  • Inspiration to the CNN
  • Architecture of CNN
  • Convolution layers in CNN
  • Filters in CNN
  • Pooling layer in CNN
  • Depth pooling in CNN
  • Different architectures of CNN
  • Single neuron RNN
  • Working with RNN neural network
  • Input and Output Sequences in RNN
  • Introduction to Deep RNN
  • Forecasting using RNN
  • Unstable gradient problem
  • Architecture of LSTM
  • Architecture of GRU
  • Introduction to Natural Language processing
  • Shakespear text generation using char RNN
  • Stateless and stateful RNN
  • Concept of sentiment analysis
  • Encoder and Decoder Network for Neural Machine Translation
  • Pre-processing required for encoder and decoder
  • Concept of Beam Search
  • Overview of attention mechanism
  • Introduction to Autoencoders and GAN
  • Efficient data representation
  • Dimensionality reduction using autoencoders
  • Introduction to stacked autoencoders
  • Training one autoencoder at a time
  • Recurrent autoencoders
  • Sparse autoencoders
  • Generative adversarial networks
  • Deep Convolutional GANs
  • Introduction to reinforcement learning
  • Learning to optimize rewards
  • Policy Search
  • Introduction to OpenAI Gym
  • Neural Network Policies
  • Credit Assignment Problem
  • Markov Decision Process
  • Q Learning
  • Deep Q Learning

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6 months from the date of delivery.
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The subscription plan is valid for 1 year from the date of purchase.
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