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Machine Learning Applications Using Python Instances Research from Healthcare, Retail, and Finance by Puneet Mathur PDF Free Download

Author of Machine Learning Applications Using Python

Puneet Mathur Advisory Board Member & Senior Machine Learning Advisor. Puneet is an skilled hands-on machine studying guide working for shoppers from giant companies to startups and on a number of initiatives involving machine studying in healthcare, retail, finance, publishing, airways, and different domains.

He’s an IIM Bangalore alumni of BAI and Machine Learning Engineer Nanodegree Graduate from Udacity. He’s additionally an open-source Python library volunteer and contributor for machine studying scikit-learn.

For the previous 6 years, he has been working as a Machine Learning Advisor for shoppers across the globe, by guiding and mentoring consumer groups caught with machine studying issues. He additionally conducts management and motivational workshops and machine studying hands-on workshops.

He’s an writer of 9 self-published books and his new two-volume ebook sequence, The Predictive Program Supervisor primarily based on Knowledge Science and Machine Learning, is his newest work.

Machine Learning Applications Contents

• Chapter 1: Overview of Machine Learning in Healthcare 
• Chapter 2: Key Technological developments in Healthcare
• Chapter 3: Implement Machine Learning in Healthcare 
• Chapter 4: Case Research in Healthcare AI
• Chapter 5: Pitfalls to Keep away from with Machine Learning in Healthcare
• Chapter 6: Monetizing Healthcare Machine Learning
• Chapter 7: Overview of Machine Learning in Retail 
• Chapter 8: Key Technological Developments in Retail
• Chapter 9: Implement Machine Learning in Retail 
• Chapter 10: Case Research in Retail AI 
• Chapter 11: Pitfalls to Keep away from With Machine Learning in Retail
• Chapter 12: Monetizing Retail Machine Learning
• Chapter 13: Overview of Machine Learning in Finance 
• Chapter 14: Key Technological Developments in Finance 
• Chapter 15: Implement Machine Learning in Finance
• Chapter 16: Case Research in Finance AI
• Chapter 17: Pitfalls to Keep away from with Machine Learning in Finance
• Chapter 18: Monetizing Finance Machine Learning

Introduction to Machine Learning Applications Using Python

The concept of scripting this ebook got here up once I was planning a machine studying workshop in Bangalore in 2016.

After I interacted with individuals, I discovered that though many mentioned they knew machine studying and had largely discovered it by means of self-study mode, they weren’t in a position to reply interviewers’ questions on making use of machine studying to sensible enterprise issues.

Even a number of the skilled machine studying professionals mentioned that they had implementation expertise of pc imaginative and prescient in a selected space like manufacturing; nonetheless, they didn’t have the experiential data on how it may be utilized in different domains.

As of the writing of this ebook, the three most progressive and promising areas for implementation are healthcare, retail, and finance.

I name them promising as a result of there are some functions which were inbuilt areas like healthcare (e.g., with skilled robotic processes like surgical operations); nonetheless, there are extra functions which might be being found day-after-day.

Retail impacts the on a regular basis lives of everyone on this planet, as you want to store to your private wants. Whether or not you purchase from a grocery retailer or a retail chain, on-line machine studying and synthetic intelligence are going to alter the shopper expertise by predicting their wants and ensuring the best options can be found on the proper time.

Finance is one other space that holds a variety of promise and has seen much less utility of machine studying and synthetic intelligence compared to the opposite sectors.

The first purpose for that’s as a result of it’s the sector with the utmost laws and legislation enforcement going down closely right here. It is usually the sector that varieties the spine of the financial system. With out finance, there isn’t any different sector that may function.

Readers, be they those that are simply beginning off with machine studying or with expertise in Python and machine studying implementation in initiatives aside from these sectors, will certainly acquire an experiential data that I share with you thru the case research introduced on this ebook.

The reader will get motivation from my well-known quote on synthetic intelligence and machine studying it isn’t the Synthetic Intelligence however the Human Intelligence behind the Synthetic Intelligence that’s going to alter the best way we stay our lives sooner or later.

There are three sections on this ebook, and I feel every of those may have been printed as separate books in themselves. The nice factor that the reader will discover is that the construction of those three sections is equivalent.

Every part begins off with an outline part the place you’ll perceive the present eventualities for that phase, reminiscent of healthcare, retail, or finance. Then there’s the technological development chapter widespread to all of the three segments, the place the state of machine studying has been mentioned intimately.

It is usually the part the place I current to you the outcomes of the Delphi Technique skilled survey for every of these domains. Then there’s a chapter on learn how to implement machine studying in that specific area.

That is the place you’ll discover ways to use an industry-emulated or modeled information set and learn how to implement it utilizing Python code, step-by-step. A few of this code and method it is possible for you to to immediately apply in your mission implementations.

In every part, one can find two case research taken from sensible enterprise issues, once more modeled on a number of the sensible enterprise issues which might be generally confronted by companies in that {industry} phase.

Every case research is exclusive and has its personal questions that you need to rigorously research and attempt to reply independently. I’ve given the answer for under one of many case research utilizing Python code, and I’ve let the second case research in every part be a discussion-only answer.

The rationale for doing it is because I would like you to use your personal thoughts to unravel them after taking a look at how I’ve solved the primary one. Please bear in mind every enterprise is totally different, and every answer has to even be totally different.

Nonetheless, the machine studying method doesn’t differ a lot. I do know for certain that a lot of you who learn this ebook are extremely skilled machine studying professionals in your discipline and that’s the reason you’re searching for skilled recommendation on learn how to keep away from widespread gotchas or pitfalls throughout machine studying in that area, reminiscent of healthcare or retail or finance.

Every sector has its personal set of pitfalls, as the character of the enterprise may be very totally different. There might be many readers who may belong to the startup eco-system and wish to get new concepts on the implementation of machine studying and synthetic intelligence in these areas.

In every of the three sections, one can find three progressive concepts that I current to you that you possibly can instantly take and begin implementing.

If you’re searching for a ebook that provides you experiential and sensible data of learn how to use Python and resolve a number of the issues in the true world, then you may be extremely happy.

Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance PDF

Author(s): Puneet Mathur

Publisher: Apress, Year: 2019

ISBN: 1484237862

Download Machine Learning Applications Using Python by Mathur PDF Free.