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 You'll be able to build deep learning models using Keras You'll learn how to evaluate the performance of neural networks built using Keras You'll 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
- You'll be able to build deep learning models using Keras
- You'll learn how to evaluate the performance of neural networks built using Keras
- You'll 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
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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
Frequently Asked Questions
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