Keras library for deep learning with Machine Learning

Keras library for deep learning with Machine Learning, available at $19.99, has an average rating of 3.5, with 51 lectures, based on 28 reviews, and has 1284 subscribers.

You will learn about Youll be able to build deep learning models using Keras Youll learn how to evaluate the performance of neural networks built using Keras Youll understand how to tune Keras layers on different network topologies. Knowledge of code of several neural networks from the ground up in Python using Keras To distinguish which practical applications can benefit from deep learning To train and run models in the cloud using a GPU To build, train and use fully connected, convolutional and recurrent neural networks To apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data To install and use Python and Keras to build deep learning models To understand and code Convolutional Neural Networks as well as graph-based deep models involving residual connections and inception modules To build a simple image recognition project using the CIFAR-10 library To build Handwritten digit recognition with advanced MNIST To Build Image recognition with CIFAR-100 This course is ideal for individuals who are If you are interested in building and tuning deep learning models in Keras then this course is for you or Anyone who knows a bit of machine learning and wants to learn deep learning (this course focuses on deep learning -Keras) or Anyone who is a researcher, software engineer or educator working in machine learning /Deep Learning and wants to move from theory to practice or Anyone who is looking for the best course on Keras deep learning It is particularly useful for If you are interested in building and tuning deep learning models in Keras then this course is for you or Anyone who knows a bit of machine learning and wants to learn deep learning (this course focuses on deep learning -Keras) or Anyone who is a researcher, software engineer or educator working in machine learning /Deep Learning and wants to move from theory to practice or Anyone who is looking for the best course on Keras deep learning.

Enroll now: Keras library for deep learning with Machine Learning

Summary

Title: Keras library for deep learning with Machine Learning

Price: $19.99

Average Rating: 3.5

Number of Lectures: 51

Number of Published Lectures: 36

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 36

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Youll be able to build deep learning models using Keras

Youll learn how to evaluate the performance of neural networks built using Keras

Youll understand how to tune Keras layers on different network topologies.

Knowledge of code of several neural networks from the ground up in Python using Keras

To distinguish which practical applications can benefit from deep learning

To train and run models in the cloud using a GPU

To build, train and use fully connected, convolutional and recurrent neural networks

To apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data

To install and use Python and Keras to build deep learning models

To understand and code Convolutional Neural Networks as well as graph-based deep models involving residual connections and inception modules

To build a simple image recognition project using the CIFAR-10 library

To build Handwritten digit recognition with advanced MNIST

To Build Image recognition with CIFAR-100

Who Should Attend

If you are interested in building and tuning deep learning models in Keras then this course is for you

Anyone who knows a bit of machine learning and wants to learn deep learning (this course focuses on deep learning -Keras)

Anyone who is a researcher, software engineer or educator working in machine learning /Deep Learning and wants to move from theory to practice

Anyone who is looking for the best course on Keras deep learning

Target Audiences

If you are interested in building and tuning deep learning models in Keras then this course is for you

Anyone who knows a bit of machine learning and wants to learn deep learning (this course focuses on deep learning -Keras)

Anyone who is a researcher, software engineer or educator working in machine learning /Deep Learning and wants to move from theory to practice

Anyone who is looking for the best course on Keras deep learning

Keras is an open source neural network library written in Python. It is capable of running on top of MXNet, Deep learning?Tensorflow, CNTK, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible.

This course provides a comprehensive expert level details in?deep learning(Keras). We start by?a brief recap of the most common concepts found in machine learning. Then, we introduce neural networks and the optimization techniques to train them. We’ll show you how to get ready with Keras API to start training deep learning models, both on CPU and on GPU. Then, we present two types of neural architecture: convolutional and recurrent neural networks

In this course,?we will start from the very scratch. This is a very applied course, so we will immediately start coding even without installation! You will see a brief bit of?absolutely essential theory?and then we will get into the environment setup and explain almost all concepts through code. You will be using?Keras? one of the easiest and most powerful machine learning tools out there.

In this course we will get started with?Keras, where?we’ll compare with TensorFlow to make it easier to understand, and to build your knowledge upon itself. By connecting new information with existing knowledge, you’ll form?stronger connections?in your brain on all of this valuable tech content. You’ll learn where and how to use Keras. By the end of this course you’ll have such a solid grasp you can add all of these technologies as qualifications on?your?resume, LinkedIn profile, or personal website.

Also we?will learn to?build a basic?image recognition model?and much much more.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Background and Foundation-Neural Networks

Lecture 3: Installation 1

Lecture 4: Installation 2

Lecture 5: Installation 3

Lecture 6: Installation 4

Chapter 2: ConvNets

Lecture 1: Lesson A

Lecture 2: Lesson B

Lecture 3: Lesson C

Lecture 4: Lesson D

Lecture 5: Lesson E

Chapter 3: GAN

Lecture 1: Theory

Lecture 2: Lesson A

Lecture 3: Lesson B

Chapter 4: Example-Image classification using Convolutional Neural Networks in Keras

Lecture 1: Lesson A

Lecture 2: Lesson B

Chapter 5: Word Embeddings

Lecture 1: Lesson A

Lecture 2: Lesson B

Lecture 3: Lesson C

Lecture 4: Lesson D

Lecture 5: Lesson E

Lecture 6: Lesson F

Chapter 6: RNN with Keras

Lecture 1: Lesson A

Lecture 2: Lesson B-Theory

Lecture 3: Lesson C

Lecture 4: Lesson D

Chapter 7: RNN -Cont.

Lecture 1: Lesson E-1

Lecture 2: Lesson E-2

Chapter 8: Exercise section

Lecture 1: ex 1

Chapter 9: Keras-API

Lecture 1: Lesson A

Lecture 2: Lesson B

Lecture 3: Lesson C

Lecture 4: Lesson D

Lecture 5: Lesson E

Lecture 6: Lesson F

Chapter 10: Concepts behind RL

Lecture 1: Lecture A

Instructors

XEH Academy
Former Instructor@ Microsoft,Cisco, GE, HP & JP Morgan Chase

Rating Distribution

1 stars: 6 votes

2 stars: 3 votes

3 stars: 2 votes

4 stars: 8 votes

5 stars: 9 votes

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