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Machine Learning
{"id":583109345324,"title":"Machine Learning with Python","handle":"machine-learning-with-python","description":"\u003cp\u003eAuthor: Abhishek Vijayvargia\u003cbr\u003ePrice: 297\u003cbr\u003eISBN: 9789386551931\u003cbr\u003ePages: 267\u003cbr\u003eEdition: 1st 2018 Paperback\u003cbr\u003eTerritory: Worldwide \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e*It includes the CD which has Machine Learning Algorithms of chapters in the Python notebook.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThis book provides the concept of machine learning with mathematical explanation and programming examples. Every chapter starts with fundamentals of the technique and working example on the real-world dataset. Along with the advice on applying algorithms, each technique is provided with advantages and disadvantages on the data.\u003c\/p\u003e\n\u003cp\u003eIn this book we provide code examples in python. Python is the most suitable and worldwide accepted language for this. First, it is free and open source. It contains very good support from open community. It contains a lot of library, so you don’t need to code everything. Also, it is scalable for large amount of data and suitable for big data technologies.\u003c\/p\u003e\n\u003cp\u003eThis book:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eCovers all major areas in Machine Learning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eTopics are discussed with graphical explanations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eComparison of different Machine Learning methods to solve any problem.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eMethods to handle real-world noisy data before applying any Machine Learning algorithm.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003ePython code example for each concept discussed.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eJupyter notebook scripts are provided with dataset used to test and try the algorithms\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c\/strong\u003e\u003cstrong\u003e\u003cspan\u003eContents\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eIntroduction to Machine Learning \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eUnderstanding Python \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eFeature Engineering \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eData Visualisation\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eBasic and Advanced Regression\u003cspan\u003e techniques\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eClassification \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eUn Supervised Learning\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eText Analysis\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eNeural Network and Deep Learning \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eRecommendation System \u003cspan\u003e \u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eTime Series Analysis \u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e","published_at":"2018-02-20T12:05:35+05:30","created_at":"2018-02-20T12:09:26+05:30","vendor":"Abhishek Vijayvargia","type":"Book","tags":["Machine Learning","Machine learning with Python","Python book"],"price":26800,"price_min":26800,"price_max":26800,"available":true,"price_varies":false,"compare_at_price":29700,"compare_at_price_min":29700,"compare_at_price_max":29700,"compare_at_price_varies":false,"variants":[{"id":7161876545580,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"5","requires_shipping":true,"taxable":false,"featured_image":null,"available":true,"name":"Machine Learning with Python","public_title":null,"options":["Default Title"],"price":26800,"weight":0,"compare_at_price":29700,"inventory_quantity":48,"inventory_management":"shopify","inventory_policy":"deny","barcode":"9789386551931"}],"images":["\/\/cdn.shopify.com\/s\/files\/1\/2228\/7547\/products\/Machine_Learning_with_Python_copy.jpg?v=1524485640"],"featured_image":"\/\/cdn.shopify.com\/s\/files\/1\/2228\/7547\/products\/Machine_Learning_with_Python_copy.jpg?v=1524485640","options":["Title"],"content":"\u003cp\u003eAuthor: Abhishek Vijayvargia\u003cbr\u003ePrice: 297\u003cbr\u003eISBN: 9789386551931\u003cbr\u003ePages: 267\u003cbr\u003eEdition: 1st 2018 Paperback\u003cbr\u003eTerritory: Worldwide \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e*It includes the CD which has Machine Learning Algorithms of chapters in the Python notebook.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThis book provides the concept of machine learning with mathematical explanation and programming examples. Every chapter starts with fundamentals of the technique and working example on the real-world dataset. Along with the advice on applying algorithms, each technique is provided with advantages and disadvantages on the data.\u003c\/p\u003e\n\u003cp\u003eIn this book we provide code examples in python. Python is the most suitable and worldwide accepted language for this. First, it is free and open source. It contains very good support from open community. It contains a lot of library, so you don’t need to code everything. Also, it is scalable for large amount of data and suitable for big data technologies.\u003c\/p\u003e\n\u003cp\u003eThis book:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eCovers all major areas in Machine Learning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eTopics are discussed with graphical explanations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eComparison of different Machine Learning methods to solve any problem.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eMethods to handle real-world noisy data before applying any Machine Learning algorithm.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003ePython code example for each concept discussed.\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eJupyter notebook scripts are provided with dataset used to test and try the algorithms\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c\/strong\u003e\u003cstrong\u003e\u003cspan\u003eContents\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eIntroduction to Machine Learning \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eUnderstanding Python \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eFeature Engineering \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eData Visualisation\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eBasic and Advanced Regression\u003cspan\u003e techniques\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eClassification \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eUn Supervised Learning\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eText Analysis\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eNeural Network and Deep Learning \u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eRecommendation System \u003cspan\u003e \u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003eTime Series Analysis \u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e"}
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Machine Learning with Python
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Author: Abhishek VijayvargiaPrice: 297ISBN: 9789386551931Pages: 267Edition: 1st 2018 PaperbackTerritory: Worldwide *It includes the CD which has Machine Learning Algorithms of chapters in...