Deep Learning using Tensorflow Training in Bangalore - ZekeLabs Best Deep Learning using Tensorflow Training Institute in Bangalore India
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs

Deep Learning using Tensorflow Training

Deep Learning using Tensorflow Course: Opensource since Nov,2015. Roots in Google Brain team.Library for doing Complex Numerical Computation to build machine learning models from scratch.It has scikit-flow similar to scikit-learn for high level machine learning API's. Tensorflow uses Directed Graph as its computational model, similar to Spark. Functions are nodes & edges data. Graph model makes it well suited for deploying Neural Networks.Data flow graph model makes it easily distributed - across CPUs, GPUs & multiple systems.Tensorboard, a visualization software along with Tensorflow makes debugging & analyzing machine learning models really easy.Pre-trained tensorflow model for small devices like mobile, raspberry pi etc makes it highly portable.TensorFlow-Serving is available for deploying pre-trained models in production. Deep Learning is heavily adopted across many companies using TensorFlow.
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Assignments
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Industry Level Projects
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Certification

Deep Learning using Tensorflow Course Curriculum



Introducing machine learning
Unsupervised learning
What is deep learning?
Deep learning history
Neural networks
An artificial neuron
The backpropagation algorithm
Stochastic gradient descent
Multilayer perceptron
Convolutional Neural Networks
Autoencoders
Deep learning framework comparisons
General overview
How does it change the way people use it?
Installing TensorFlow on Linux
Requirements for running TensorFlow with GPU from NVIDIA
Installing TensorFlow with native pip
Installing TensorFlow on Windows
Install on Windows
Computational graphs
Neural networks as computational graphs
Data model
Shape
Variables
Feeds
How does TensorBoard work?
Source code for the single input neuron
How to upgrade using the script
Upgrading code manually
Functions
Miscellaneous changes
Introducing feed-forward neural networks
Weights and biases
Classification of handwritten digits
Softmax classifier
How to save and restore a TensorFlow model
Restoring a model
Softmax loader source code
Visualization
ReLU classifier
Source code for the ReLU classifier
Visualization
Introducing CNNs
A model for CNNs - LeNet
Source code for a handwritten classifier
Source code for emotion classifier
Source code
Introducing autoencoders
Source code for the autoencoder
Building a denoising autoencoder
Convolutional autoencoders
Decoder
RNNs basic concepts
Unfolding an RNN
LSTM networks
Source code for RNN image classifier
Source code for the bidirectional RNN
Dataset
PTB model
GPGPU computing
The CUDA architecture
TensorFlow GPU set up
TensorFlow GPU management
Source code for GPU computation
Assigning a single GPU on a multi-GPU system
Using multiple GPUs
Introducing Keras
Building deep learning models
Source code for the Keras movie classifier
Source code for movie classifier with convolutional layer
Chaining layers
Sequential mode
Digit classifier
TFLearn
Titanic survival predictor
Introduction to multimedia analysis
Bottlenecks
Accelerated Linear Algebra
Just-in-time compilation via XLA
Existence and advantages of XLA
Still experimental
More experimental material
What is Keras?
Video question answering system
Deep learning on Android
Getting started with Android
Prebuilt APK
Building with Android studio
Basic concepts of Reinforcement Learning
Introducing the OpenAI Gym framework
Source code for the FrozenLake-v0 problem
Source code for the Q-learning neural networ

Frequently Asked Questions


We provide classroom-based as well as online training. Since this is a hand-on training so batches generally does not contain more than 4 people.

We will provide web services specific study material as the course progresses. You will have lifetime access to all the code and basic settings needed for these Deep Learning using Tensorflow through our github account and the study material that we share with you. You can use that for quick reference.

Feel free to drop a mail to us at support@zekelabs.com and we will get back to you at the earliest for your queries on Deep Learning using Tensorflow course

We have tie ups with various companies and placement organizations to whom we connect our learners. Each Deep Learning using Tensorflow training ends with career consulting

Minimum 2-3 projects of industry standards on Deep Learning using Tensorflow will be provided

Yes, we provide our own course completion certificate to all students. Each Deep Learning using Tensorflow training in bangalore ends with training and project completion certificate

You can pay by card (debit/credit), cash, cheque and net-banking. You can pay in two installments

We take immense pride to provide post training career consulting for Deep Learning using Tensorflow training



Recommended Courses


Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Hadoop - Mastering Big Data with Hadoop Ecosystem
  More Info  
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Spring 4.0 - A Deep Dive
  More Info  
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Hibernate
  More Info  
Feedback