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Intro to Deep Learning With TensorFlow
Duration
3 Days
Course
DCSK-120
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Intro to Deep Learning With TensorFlow course is designed to introduces Deep Learning concepts and Tensorflow library to students.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.
Objectives
Upon completion of the Intro to Deep Learning With TensorFlow course, students will be able to:
- Introduction to Machine Learning
- Deep Learning concepts
- Tensorflow library
- Writing Tensorflow applications (CNN, RNN)
- Using TF tools
- High level libraries : Keras
Audience
- Developers, Data analysts, data scientists
Prerequisites
- 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.
Topics
Introduction to Machine Learning
- Understanding Machine Learning
- Supervised versus Unsupervised Learning
- Regression
- Classification
- Clustering
- Tensorflow intro
- Tensorflow Features
- Tensorflow Versions
- GPU and TPU scalability
- Lab: Setting up and Running Tensorflow
- Introducing Tensors
- Tensorflow Execution Model
- Lab: Learning about Tensors
- Introducing Perceptrons
- Linear Separability and Xor Problem
- Activation Functions
- Softmax output
- Backpropagation, loss functions, and Gradient Descent
- Lab: Single-Layer Perceptron in Tensorflow
- Hidden Layers as a solution to XOR problem
- Distributed Training with Tensorflow
- Vanishing Gradient Problem and ReLU
- Loss Functions
- Lab: Feedforward Neural Network Classifier in Tensorflow
- Using high level tensorflow
- Developing a model with tf.learn
- Lab: Developing a tf.learn model
- Introducing CNNs
- CNNs in Tensorflow
- Lab : CNN apps
- What is Keras?
- Using Keras with a Tensorflow Backend
- Lab: Example with a Keras
- Introducing RNNs
- RNNs in Tensorflow
- Lab: RNN
- Introducing RNNs
- RNNs in Tensorflow
- Lab: RNN
- Summarize features and advantages of Tensorflow
- Summarize Deep Learning and How Tensorflow can help
- Next steps
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- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
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Please take a moment to fill out this form. We will get back to you as soon as possible.
All fields marked with an asterisk (*) are mandatory.