Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product]

Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen

Building Machine Learning Powered Applications: Going from Idea to Product Free read à 106 Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Read & Download Building Machine Learning Powered Applications: Going from Idea to Product O improve the model until it fulfills your original vision Part IV covers deployment and monitoring strategies This book will help you Define your product goal and set up a machine learning problem Build your first end to end pipeline uickly and acuire an initial dataset Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your models in a production environme. This book is introductory and superficial Probably good for aspiringjunior data scientists but not very interesting for experienced practitioners

Read & Download Building Machine Learning Powered Applications: Going from Idea to ProductBuilding Machine Learning Powered Applications: Going from Idea to Product

Building Machine Learning Powered Applications: Going from Idea to Product Free read à 106 Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Read & Download Building Machine Learning Powered Applications: Going from Idea to Product Learn the skills necessary to design build and deploy applications powered by machine learning ML Through the course of this hands on book you'll build an example ML driven application from initial idea to deployed product Data scientists software engineers and product managers including experienced practitioners and novices alike will learn the tools best practices and challenges involved in bu. I don t think the author has built a machine learning powered application This book is extremely lightweight at a little over 200 pages and is too high level to have any practicality The content is just an odd assortment of stuff with bizarre sidebars on transfer learning and code snippets with no cohesiveness The chapter on deployment is exactly ten pages long and is a big nothing burger I don t even recommend this book for a beginner because it will confuse them

Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen

Building Machine Learning Powered Applications: Going from Idea to Product Free read à 106 Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Read & Download Building Machine Learning Powered Applications: Going from Idea to Product Ilding a real world ML application step by step Author Emmanuel Ameisen an experienced data scientist who led an AI education program demonstrates practical ML concepts using code snippets illustrations screenshots and interviews with industry leaders Part I teaches you how to plan an ML application and measure success Part II explains how to build a working ML model Part III demonstrates ways t. I will start off by saying on a scale of 1 to 10 in data science machine learning knowledge 1 being I barely know what a linear model is and 10 being I contribute to building Machine Learning Libraries conduct research that I am around a 4 I initially bought this book because I have a decent understanding of Data Science created a few models at work and personally and was interested in ways to serve the model via webserver like flaskdjangoThe best analogy I can give about this book is its like going to a restaurant seeing beef stew on the menu and ordering it When it arrives you realize it is just beef broth and when you complain to the waiter they tell you beef was stewed in it but you have to pay extra for the actual beef Hence the title of my reviewChapter after chapter I kept waiting for him to dive into the python scripts and explaining how they build the model In this 250 page book maybe 30 of the pages are dedicated to explaining the model and pipeline with the rest dedicated to superficially explaining DSML conceptsIt doesn t go deep enough for anyone who has an intermediate level of knowledge DSML On the other hand it doesn t explain enough for people who might be beginners For example it just assumes you understand when to apply XGBoost versus using Scikit Learn But then on the next page it tries to explain the K Nearest Neighbors algorithm Like you are expecting the reader to understand how different Machine Learning libraries affect computational needs but then assume they don t know the most basic clustering algorithm WhatTo me it feels like a hastily written half white paperhalf wiki article about DSML algorithms Computer Science and how Machine Learning is actually bad for humanityAlso he interviews people who have DSML experience which is a good idea and cool in theory but some of the interviews just feel like sales pitches for their products Like I haven t used StictchFix and it might be a great product but I will go to their website to learn about it I don t want to pay to read a sales pitchI wish I could return this book but have already highlighted it from from to back Please don t buy this book unless you fall into whatever very niche group this author targeted the book towards Instead buy Hands on Machine Learning if you want to learn about DSML If you want to know how to deploy your models maybe try Applied Data Science 20 but due to version updates and dependencies I couldn t get it to deploy but the reference on how to build the pipeline is usefulTo me this book felt like a lot of bad Medium or Towards Data Science articles stacked on top of each other


5 thoughts on “Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product]

  1. says: Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] Read & Download Building Machine Learning Powered Applications: Going from Idea to Product

    Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Emmanuel Ameisen é 6 characters Read & Download Building Machine Learning Powered Applications: Going from Idea to Product I don't think the author has built a machine learning powered application This book is extremely lightweight at a little over 200 pages and is too high level to have any practicality The content is just an odd assortment of stuff with bizarre sidebars on transfer learning and code snippets with no cohesiveness The chapter on deploym

  2. says: Emmanuel Ameisen é 6 characters Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Read & Download Building Machine Learning Powered Applications: Going from Idea to Product

    Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] I will start off by saying on a scale of 1 to 10 in data science machine learning knowledge 1 being I barely know what a linear model is and 10 being I contribute to building Machine Learning Libraries conduct research that I am around a 4 I initially bought this book because I have a decent understanding of Data Science c

  3. says: Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product]

    Free download ✓ PDF, eBook or Kindle ePUB é Emmanuel Ameisen Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] This book is introductory and superficial Probably good for aspiringjunior data scientists but not very interesting for experienced practitioners

  4. says: Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] Emmanuel Ameisen é 6 characters Read & Download Building Machine Learning Powered Applications: Going from Idea to Product

    Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] This book is NOT an overly technical book The way I read it it's a book that's centered around the lessons the author Emmanuel learned during his time as a data scientistML engineer He formats these lessons in such a way that makes the book e

  5. says: Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product]

    Pdf/E–book [Building Machine Learning Powered Applications: Going from Idea to Product] I've met a lot of people who would say they are well aware of the contents of this book and that they would have nothing to learn from reading it But it amazes me how many times I've seen those people spin up projects and completely ignore the steps they claim to know If you're managing a team I think this should

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  • null
  • Building Machine Learning Powered Applications: Going from Idea to Product
  • Emmanuel Ameisen
  • English
  • 14 May 2020
  • 149204511X