TensorFlow Training

(3) 3 Ratings

Course Schedule

30

JUL

Mon - Sat

07:30 PM - 10:00 PM ( IST )

06

AUG

Mon - Fri

11:00 AM - 02:00 PM ( IST )

11

AUG

Sat - Sun

05:30 AM - 06:30 AM ( IST )


Total Learners

880 Learners


LMS Access

365 days

Course duration

30 days


Support

24/7 support

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The Instructor for this course is from one of the Big5 Companies in the world.

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Modes of Training

Corporate Training

Live, Classroom Or Self Paced Training

Online Classroom

Attend our Instructor Led Online Virtual Classroom

Self Paced Training

Comprehensive Recorded Videos by Experts to learn at your own pace

Course Features

Live Instructor-led Classes

This isn't canned learning. Its dynamic, its interactive, its effective

Expert Educators

Only the best or they're out. We are constantly evaluating our trainers

24&7 Support

We never sleep. Need something answered at 3 am? No Problem

Flexible Schedule

You don't learn as per our calendar. We work according to yours

☰ Details

Course Curriculum

Introduction To Deep Learning

The Math behind Machine Learning: Linear Algebra

  • Scalars
  • Vectors
  • Matrices
  • Tensors
  • Hyperplanes

The Math Behind Machine Learning: Statistics

  • Probability
  • Conditional Probabilities
  • Posterior Probability
  • Distributions
  • Samples vs Population
  • Resampling Methods
  • Selection Bias
  • Likelihood

Review of Machine Learning Algorithms

  • Regression
  • Classification
  • Clustering
  • Reinforcement Learning
  • Underfitting and Overfitting
  • Optimization
  • Convex Optimization.

Fundamentals Of Neural Networks

  • Defining Neural Networks
  • The Biological Neuron
  • The Perceptron
  • Multi-Layer Feed-Forward Networks
  • Training Neural Networks
  • Backpropagation Learning
  • Gradient Descent
  • Stochastic Gradient Descent
  • Quasi-Newton Optimization Methods
  • Generative vs Discriminative Models

Activation Functions

  • Linear
  • Sigmoid
  • Tanh
  • Hard Tanh
  • Softmax
  • Rectified Linear
  • Loss Functions
  • Loss Function Notation
  • Loss Functions for Regression
  • Loss Functions for Classification
  • Loss Functions for Reconstruction
  • Hyperparameters
  • Learning Rate
  • Regularization
  • Momentum
  • Sparsity.

Fundamentals Of Deep Networks

  • Defining Deep Learning
  • Defining Deep Networks
  • Common Architectural Principals of Deep Networks
  • Reinforcement Learning application in Deep Networks
  • Parameters
  • Layers
  • Activation Functions – Sigmoid, Tanh, ReLU
  • Loss Functions
  • Optimization Algorithms
  • Hyperparameters
  • Summary 

Introduction To TensorFlow

  • What is TensorFlow?
  • Use of TensorFlow in Deep Learning
  • Working of TensorFlow
  • How to install Tensorflow
  • HelloWorld with TensorFlow
  • Running a Machine learning algorithms on TensorFlow.

Convolutional Neural Networks (CNN)

  • Introduction to CNNs
  • CNNs Application
  • Architecture of a CNN
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN
  • Transfer Learning and Fine-tuning Convolutional Neural Networks. 

Recurrent Neural Networks (RNN)

  • Introduction to RNN Model
  • Application use cases of RNN
  • Modelling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model. 

Restricted Boltzmann Machine(RBM) And Autoencoders

  • Restricted Boltzmann Machine
  • Applications of RBM
  • Collaborative Filtering with RBM
  • Introduction to Autoencoders
  • Autoencoders applications
  • Understanding Autoencoders
  • Variational Autoencoders
  • Deep Belief Network 

Course Description

What are the Course Objectives of Training?

  • Understand how Neural Networks Work.
  • Use TensorFlow for Classification and Regression Tasks.
  • Use TensorFlow for Time series Analysis with Recurrent Neural Networks.
  • Learn how to Conduct Reinforcement  and learn with OpenAI Gym.
  • Become a DeepLearning Guru.

What are Pre-requisites for this Training Course?

  • Some knowledge of programming (preferably Python)
  • Some basic knowledge of math (mean, standard deviation, etc..)

Who Should Attend this Training?

The following professionals can go for this course:

  • Developers aspiring to be a 'Data Scientist'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Deep Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • Professionals who want to captivate and analyze Big Data
  • Analysts wanting to understand Data Science methodologies
However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

FAQ

Do you have self paced training?

Yes, we offer self paced training

How do you provide training?

We offer three different modes of training. Instructor Led Live Training, Self Paced Training and Corporate Training

Do you offer any discounts?

Yes we offer discounts for group of 3 plus people.

Can I choose timings that suits my schedule?

Yes we are the only company where we work with students and offer flexible timings which fits your schedule

Who are the Instructors?

All our instructors are from MNC companies who have real time experience of more than 10 years.

Can I attend a demo session before joining?

Yes we offer a free demo session with the instructors. The trainer will answer all your queries and share the course agenda.

Course Reviews

Sukesh

It is a great experience to learn online courses from Live Trainings Bangalore. The sessions are very professional. I had enrolled for TensorFlow course. It helped me a lot professionally at my work place. I am very glad for choosing LTB as my learning partner. Thank you.

Tapasya

Hi, I am new to TensorFlow and this course contains a very good explanation for the beginner to understand the Process. Thanks to the Trainer.

Sujatha

Well, I took TensorFlow online training course from Live Trainings Bangalore and now I am an expert in Course. Industry expert trainers, great format, clear explanations, extremely well presented and overall completely satisfactory. Trust me guys, you will love this training. Highly recommended!