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
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

Setting up a deep learning environment
Installing Anaconda and libraries
Intuitively building networks with Keras
Tensorflow Basic Operations-A simple example that cover TensorFlow basic operations.
Tensorflow Logistic Regression-Implement a Logistic Regression with TensorFlow.
Tensorflow K-Means-Build a K-Means classifier with TensorFlow.
Understanding the perceptron
Building a multi-layer neural network
Hidden layers and hidden units
Tuning the loss function
Improving generalization with regularization
Tensorflow Simple Neural Network-MNIST
Getting started with filters and parameter sharing
Optimizing with batch normalization
Experimenting with different types of initialization
Applying a 1D CNN to text
Tensorflow Convolutional Neural Network (tf.layers/estimator api)-MNIST
Implementing a simple RNN
Using gated recurrent units (GRUs)
Tensorflow Bi-directional Recurrent Neural Network (LSTM)-MNIST
Understanding GANs
Upscaling the resolution of images with Super Resolution GANs (SRGANs)
Tensorflow DCGAN (Deep Convolutional Generative Adversarial Networks)
Augmenting images with computer vision techniques
Localizing an object in images
Scene understanding (semantic segmentation)
Recognizing faces
Analyzing sentiment
Summarizing text
Visualizing training with TensorBoard and Keras
Using grid search for parameter tuning
Comparing optimizers
Adding dropouts to prevent overfitting
Visualizing training with TensorBoard
Freezing layers
Large-scale visual recognition with GoogLeNet/Inception
Leveraging pretrained VGG models for new classes
CIFAR 10 image classification

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 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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