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Lessons List | 36 Lesson
Cloud Computing Course Introduction Lesson 01
00:02:40

Cloud Computing Course Introduction Lesson 01
Defining a Cloud Lesson 02
00:08:11

Defining a Cloud Lesson 02
Why use cloud computing Lesson 03
00:12:02

Why use cloud computing Lesson 03
What is virtualization technology Lesson 04
00:11:36

What is virtualization technology Lesson 04
What is a network Lesson 05
00:07:41

What is a network Lesson 05
What is compute instance Lesson 06
00:04:31

What is compute instance Lesson 06
Fundamentals of Machine Learning Lesson 07
00:03:58

Fundamentals of Machine Learning Lesson 07
What is a neuron in machine learning Lesson 08
00:04:20

What is a neuron in machine learning Lesson 08
What are Weights in Machine Learning Lesson 09
00:08:44

What are Weights in Machine Learning Lesson 09
What are Biases in Machine Learning Lesson 10
00:07:23

What are Biases in Machine Learning Lesson 10
Hardware Requirements for Machine Learning Lesson 11
00:08:10

Hardware Requirements for Machine Learning Lesson 11
Machine Learning Model Introduction Lesson 12
00:03:57

Machine Learning Model Introduction Lesson 12
What is the MNIST dataset Lesson 13
00:07:34

What is the MNIST dataset Lesson 13
Creating a Compute Instance on Google Cloud Platform Lesson 14
00:12:02

Creating a Compute Instance on Google Cloud Platform Lesson 14
How to implement Machine Learning Model Lesson 15
00:19:07

How to implement Machine Learning Model Lesson 15
How do you train a model in machine learning Lesson 16
00:04:53

How do you train a model in machine learning Lesson 16
Basics of HTTP requests Lesson 17
00:07:33

Basics of HTTP requests Lesson 17
What is an API Lesson 18
00:08:07

What is an API Lesson 18
Documentation of API Lesson 19
00:11:18

Documentation of API Lesson 19
Request of HTTP requests Lesson 20
00:07:08

Request of HTTP requests Lesson 20
How to Download and Install Postman Lesson 21
00:00:59

How to Download and Install Postman Lesson 21
How to use postman for making Requests Lesson 22
00:10:20

How to use postman for making Requests Lesson 22
App Engine Section Introduction Lesson 23
00:03:40

App Engine Section Introduction Lesson 23
How do I install Google App Engine Lesson 24
00:06:36

How do I install Google App Engine Lesson 24
How do I create a content delivery network Lesson 25
00:08:43

How do I create a content delivery network Lesson 25
App Engine initialization Lesson 26
00:04:10

App Engine initialization Lesson 26
How do you write an app code Lesson 27
00:11:43

How do you write an app code Lesson 27
Running the App Lesson 28
00:05:44

Running the App Lesson 28
How do you deploy a remote server code Lesson 29
00:02:27

How do you deploy a remote server code Lesson 29
Guide to app architecture Lesson 30
00:05:38

Guide to app architecture Lesson 30
App Engine config file Lesson 31
00:08:02

App Engine config file Lesson 31
App yaml configuration file Lesson 32
00:04:01

App yaml configuration file Lesson 32
What are Jinja templates Lesson 33
00:03:16

What are Jinja templates Lesson 33
How to create a form in HTML Lesson 34
00:16:54

How to create a form in HTML Lesson 34
Variables in HTML Lesson 35
00:08:31

Variables in HTML Lesson 35
How to add static stylesheet Lesson 36
00:03:32

How to add static stylesheet Lesson 36

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Gopika.R

It's very useful for me. This video helps me to understand about cloud computing in machine learning 2024-06-01

Makarand Murlidhar Mahankal

it was excllent 2024-05-14

Ugyen Dorji

Informative 2024-05-13

Melki shedek

Ok I can understand easily 2024-03-27

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Course Description

Machine Learning Hardware course, in this course we will explore the realm of machine learning hardware, covering essential components, architectures, and optimization techniques. From understanding GPU and CPU requirements to exploring specialized hardware like TPUs, FPGAs, and ASICs, you'll gain insights into selecting, configuring, and maximizing hardware resources for machine learning tasks. Whether you're a data scientist, developer, or technology enthusiast, this course provides a comprehensive understanding of the hardware infrastructure necessary for efficient and scalable machine learning solutions.
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