EncartaLabs

Deep Learning With TensorFlow

( Duration: 5 Days )

Deep Learning With TensorFlow training course is designed to introduces Deep Learning concepts and Tensorflow library to delegates. This course teaches various complex algorithms for deep learning with examples that use different deep neural networks. Delegates will also learn how to train machine to craft new features to make sense of deeper layers of data. In this course, delegates will come across topics like logistic regression, convolutional neural networks, advanced multilayer perceptrons and how to implement them using real-world datasets.

The abundance of data and affordable cloud scale has led to an explosion of interest in Deep Learning. Google has released an excellent library called Tensorflow to open-source, allowing state-of-the-art machine learning done at scale, complete with GPU-based acceleration.

By attending Deep Learning With TensorFlow workshop, delegates will learn:

  • Introduction to Machine Learning
  • Deep Learning concepts
  • Tensorflow library
  • Writing Tensorflow applications (CNN, RNN)
  • Using TF tools
  • High level libraries : Keras

  • Basic knowledge of Python language and Jupyter notebooks is assumed.
  • Basic knowledge of Linux environment would be beneficial
  • Some Machine Learning familiarity would be nice, but not necessary.
  • Developers, Data Analysts, Data Scientists

COURSE AGENDA

1

Introduction to Machine Learning

  • Understanding Machine Learning
  • Supervised versus Unsupervised Learning
  • Regression
  • Classification
  • Clustering
2

Introducing Tensorflow

  • Tensorflow intro
  • Tensorflow Features
  • Tensorflow Versions
  • GPU and TPU scalability
3

The Tensor: The Basic Unit of Tensorflow

  • Introducing Tensors
  • Tensorflow Execution Model
4

Single Layer Linear Perceptron Classifier With Tensorflow

  • Introducing Perceptrons
  • Linear Separability and Xor Problem
  • Activation Functions
  • Softmax output
  • Backpropagation, loss functions, and Gradient Descent
5

Hidden Layers: Intro to Deep Learning

  • Hidden Layers as a solution to XOR problem
  • Distributed Training with Tensorflow
  • Vanishing Gradient Problem and ReLU
  • Loss Functions
6

High level Tensorflow: tf.learn

  • Using high level tensorflow
  • Developing a model with tf.learn
7

Convolutional Neural Networks in Tensorflow

  • Introducing CNNs
  • CNNs in Tensorflow
8

Introducing Keras

  • What is Keras?
  • Using Keras with a Tensorflow Backend
9

Recurrent Neural Networks in Tensorflow

  • Introducing RNNs
  • RNNs in Tensorflow
10

Long Short Term Memory (LSTM) in Tensorflow

  • Introducing RNNs
  • RNNs in Tensorflow
11

Conclusion

  • Summarize features and advantages of Tensorflow
  • Summarize Deep Learning and How Tensorflow can help

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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