Bundle Course - Deep Learning (Foundation - Keras - TensorFlow)

Uplatz offers this comprehensive bundle course on Deep Learning consisting of a combo of video courses on all topics that are associated with Deep Learning. You will be awarded Course Completion Certificate at the end of the course.

Courses included in this Bundle Course are -

1) Deep Learning Foundation

2) Deep Learning with Keras

3) Deep Learning using Tensor Flow

Deep Learning Foundation: Deep Learning also known as Deep Structured Learning is a subset of machine learning and refers to neural networks that have the ability to learn the input data increasingly abstract representations. Artificial Intelligence and Deep Learning is revolutionizing technology, business, services and industry in a manner not seen before. This has been possible due to rapid progress and strides made in the computing and graphic processor technologies and widespread use of the internet and mobile devices.

Deep Learning with Keras: Deep Learning essentially means training an Artificial Neural Network (ANN) with a huge amount of data. In deep learning, the network learns by itself and thus requires humongous data for learning. Keras is high-level neural networks API that runs on top of TensorFlow an end to end open source machine learning platform. Using Keras, easily define complex ANN architectures to experiment on your big data. This course, Deep Learning with Keras, will get up to speed with both the theory and practice of using keras to implement deep neural networks.

Deep Learning using Tensor Flow: TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Bundle Course - Deep Learning (Foundation - Keras - TensorFlow) – Course Syllabus

Deep Learning Foundation – Course Syllabus

1: Introduction to deep learning

Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.

2: Neural Networks Basics

Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.

3: Shallow neural networks

Learn to build a neural network with one hidden layer, using forward propagation and back propagation.

4: Deep Neural Networks

Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply it to computer vision.

Deep Learning with Keras - Course Syllabus

Introduction to Deep Learning &Keras

1) What is deep learning?

2) What is ANN?

3) Introduction to Keras
· Overview of Keras
· Features of Keras
· Benefits of Keras

4) Keras Installation

Keras - Models, Layers and Modules

1) Keras Models
· Sequential Model
· Functional API

2) Keras Layers
· Core Layers
· Convolution Layers
· Pooling Layers
· Recurrent Layers

3) Modules

Keras - Model Compilation, Evaluation and Prediction

1) Loss

2) Optimizer

3) Metrics

4) Compile the model

5) Model Training

6) Model Evaluation

7) Model Prediction

Life-Cycle for Neural Network Models in Keras

1) Define Network

2) Compile Network

3) Fit Network

4) Evaluate Network

5) Make Predictions

Developing a Deep Learning model with Keras

Building our first neural network in keras

Deep Learning with TensorFlow - Course Syllabus

Module 1 – Introduction to TensorFlow

• HelloWorld with TensorFlow
• Linear Regression
• Nonlinear Regression
• Logistic Regression
• Activation Functions

Module 2 – Convolutional Neural Networks (CNN)

• CNN History
• Understanding CNNs
• CNN Application

Module 3 – Recurrent Neural Networks (RNN)

• Intro to RNN Model
• Long Short-Term memory (LSTM)
• Recursive Neural Tensor Network Theory
• Recurrent Neural Network Model

Module 4 - Unsupervised Learning

• Applications of Unsupervised Learning
• Restricted Boltzmann Machine
• Collaborative Filtering with RBM

Module 5 - Autoencoders

• Introduction to Autoencoders and Applications
• Autoencoders
• Deep Belief Network

Everyone

Passion & determination to achieve big goals in life!

• Deep Learning Engineer
• Machine Learning Engineer
• Data Scientist
• Deep Learning Scientist
• Software & Application Developer
• Data Analyst
• AI & ML Researcher
• Data Analyst
• Data Engineer

Currently there are no Q&As for this course. Be the first to ask a question.

Uplatz Certificate of Completion

Digital certificate - Included