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
Deep Learning using Tensorflow-training-in-bangalore-by-zekelabs
Industry Level Projects
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

Frequently Asked Questions

We have options for classroom-based as well as instructor led live online training. The online training is live and the instructors screen will be visible and voice will be audible. Your screen will also be visible and you can ask queries during the live session.

The training on "Deep Learning using Tensorflow" course is a hands-on training. All the code and exercises will be done in the live sessions. Our batch sizes are generally small so that personalized attention can be given to each and every learner.

We will provide course-specific study material as the course progresses. You will have lifetime access to all the code and basic settings needed for this "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 [email protected] and we will get back to you at the earliest for your queries on "Deep Learning using Tensorflow" course.

We have tie-ups with a number of hiring partners and and placement assistance companies to whom we connect our learners. Each "Deep Learning using Tensorflow" course ends with career consulting and guidance on interview preparation.

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

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

You can pay by card (debit/credit), cash, cheque and net-banking. You can also pay in easy installments. You can reach out to us for more information.

We take pride in providing post-training career consulting for "Deep Learning using Tensorflow".

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