Deep Learning using Tensorflow-training-in-singapore-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
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
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Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs

Deep Learning using Tensorflow Course Curriculum

Introduction to Deep Learning
Introduction to Tensorflow and Keras
Solution of Equations, row and column Interpretation
Partial Derivative of Polynomial and Two conditions for Local Minima
Matrix Vector Multiplication
Linear Independence and Rank of Matrix
Intuition behind Linear Regression, classification
Gradient Descent
Metrics ROC Curve, Precision Recall Curve
Evolution of Perceptrons, Hebbs Principle, Cat Experiment
Tensorflow Code
Back propagation, Dynamic Programming
Function Approximator
Dropout and Activation
1D and 2D Convolution
Convolution Layer
Learning Sharpening using single convolution Layer in Tensor-Flow
Batch Normalization
Creating Batch in Tensorflow and Normalize
Understanding a pre-trained Inception Architecture
Finetuning last layers of CNN Model
Adding a new class in the last Layer
Finetune Imagenet for Cats vs Dog Classification.
Different types of problem in Objects
YOLO v1-v3
Image Compression Simple Autoencoder
Variational Autoencoder and Reparematrization Trick
Evolution of Recurrent Structures
Learning a Sine Wave using RNN in Tensorflow
Generative vs Discrimative Models
Simple Distribution Generator in Tensorflow using MCMC (Markov Chain Monte Carlo)
InfoGANs, CycleGANs and Progressive GANs
Model Free Prediction
Model Free Control with REINFORCE and SARSA Learning
Off policy vs On Policy Learning
Q Learning
Understanding Deep Learning as Function Approximator
Revisiting Point Collector Example in Unity and
Face Detection using Yolo-v3
Real-time Depth Prediction and Pose Estimation
Tips and Tricks for scaling and easy Deployment of Deep Learning Models

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Frequently Asked Questions

This "Deep Learning using Tensorflow" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.

Participants will be provided "Deep Learning using Tensorflow"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Deep Learning using Tensorflow". Our public GitHub repository and the study material will also be shared with the participants.

All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Deep Learning using Tensorflow" training.

The "Deep Learning using Tensorflow" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Deep Learning using Tensorflow" course duration.

The "Deep Learning using Tensorflow" training is organised at the client's premises. We have delivered and continue to deliver "Deep Learning using Tensorflow" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.

Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.

Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.

Drop a mail to us at or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Deep Learning using Tensorflow" course.

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