Build &Deploy Machine Learning on Flask,AWS,Azure,Heroku,GCP

对构建数据科学和机器学习项目并在 AWS、Google Cloud、Microsoft Azure、Heroku、Flask、Streamlit 等平台上进行部署感兴趣？

有兴趣以实用的方式学习它吗？

那么这门课程适合你！！

本课程由行业专家精心设计，旨在通过实践项目和整个课程的部署，提供学习数据科学和机器学习的最佳方式。

本课程将逐步教授如何在云中部署您的机器学习模型，就像在行业中所做的那样。

我们将逐步引导您完成每个主题，解释每一行代码以供您理解。

将会有很多有趣、激动和强大的项目来更好地理解每个主题下的每个概念。

我们以这种方式构建了课程：

项目部署教程

Streamlit 项目教程

Flask 部署项目教程

Heroku 部署项目教程

谷歌云部署项目教程

AWS 部署项目教程

Microsoft Azure 部署项目教程

本课程旨在帮助初学者和中级数据科学爱好者，在项目实践中学习部署机器学习模型的最有效方法，以更好地理解课程。

本课程适用于：
任何对数据科学和机器学习感兴趣的人。
任何想要在 Flask、Heroku、AWS、谷歌云、Microsoft Azure、Streamlit 上构建和部署机器学习模型的
任何人 任何对数据科学和机器学习职业感兴趣的学生
任何有兴趣开始他们的数据科学和机器学习职业的初学者机器学习
任何了解 Python、统计学、机器学习基础知识并想了解更多关于模型部署的中级学习者
任何想要过渡到数据科学和机器学习的数据分析师 任何想要过渡到数据科学和机器的
业务分析师学习
任何对自己的工作不满意并正在寻求职业转型以成为数据科学家的人。
任何想要在他的案例场景中利用数据力量的人。
任何好奇的心

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.55 GB | Duration: 11h 58m

What you’ll learn
Learn How To Build and Deploy Machine Learning on Flask, Heroku, AWS, Google Cloud,Microsoft Azure, Streamlit
Master Machine Learning With Python
Learn Through 6 Core Industry Platforms
Learn Through Projects and Assignments
Beginner To Advance
End-to-End Data Science and Machine Learning Deployment

Description
Interested in the field of Data Science and Machine Learning?

Interested in Building Data Science and Machine Learning Projects and Deploy on Platforms such as AWS, Google Cloud, Microsoft Azure, Heroku, Flask, Streamlit?

Interested in learning it the practical way?

Then this course is for you!!

This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects and Deployment throughout the course.

This course will teach step-by-step how to deploy your machine learning models in the cloud as it is done in the industry.

We will walk you through step-by-step on each topic explaining each line of code for your understanding.

There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.

We have structured the course in this way:

Projects Deployment Tutorial

Streamlit project tutorial

Flask deployment project tutorial

Heroku deployment project tutorial

Google cloud deployment project tutorial

AWS deployment project tutorial

Microsoft Azure deployment project tutorial

This course aims to help beginners, as well as intermediate data science enthusiasts, learn the most efficient ways to deploy their machine learning models while practicing on the projects to gain a better understanding of the course.

Who this course is for:
Anyone interested in Data Science and Machine Learning.
Anyone who wants to Build And Deploy machine learning models on Flask, Heroku, AWS,Google Cloud, Microsoft Azure, Streamlit
Any student interested in a career in Data Science and Machine Learning
Any beginner level interested to kick-start their career in Data Science and Machine
 Learning
Any intermediate level learner who know the basics of python, statistics, machine
 Learning and want to learn more about model deployment
Any data analysts who want to transition to Data Science and Machine Learning
Any Business Analysts who want to transition to Data Science and Machine
 Learning
Anyone not satisfied with their job and looking for a career transition to become a
 Data Scientist.
Anyone who wants to leverage the power of data in his case scenario.
Any curious mind