{"product_id":"data-science-bookcamp-pfive-real-world-python-projects-paperback-p","title":"Data Science Bookcamp (Paperback)","description":"\u003cp\u003e\u003cspan class=\"a-text-bold\" style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-weight:\u003eLearn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science.\u003c\/span\u003e\u003cspan style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eIn\u003c\/strong\u003e\u003c\/span\u003e\u003cstrong\u003e\u003cspan class=\"a-text-italic\" style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-style: italic\u003e Data Science Bookcamp\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e\u003cstrong\u003e you will learn:\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e    Techniques for computing and plotting probabilities\u003cbr style=\"box-sizing: border-box;\"\u003e    Statistical analysis using Scipy\u003cbr style=\"box-sizing: border-box;\"\u003e    How to organize datasets with clustering algorithms\u003cbr style=\"box-sizing: border-box;\"\u003e    How to visualize complex multi-variable datasets\u003cbr style=\"box-sizing: border-box;\"\u003e    How to train a decision tree machine learning algorithm\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003eIn \u003c\/span\u003e\u003cspan class=\"a-text-italic\" style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-style: italic\u003eData Science Bookcamp\u003c\/span\u003e\u003cspan style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e you’ll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003ePurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eAbout the technology\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003eA data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eAbout the book\u003c\/strong\u003e\u003c\/span\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cspan class=\"a-text-italic\" style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-style: italic\u003eData Science Bookcamp\u003c\/span\u003e\u003cspan style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e doesn’t stop with surface-level theory and toy examples. As you work through each project, you’ll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don’t quite fit the model you’re building. You’ll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you’ll be confident in your skills because you can see the results.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eWhat's inside\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e    Web scraping\u003cbr style=\"box-sizing: border-box;\"\u003e    Organize datasets with clustering algorithms\u003cbr style=\"box-sizing: border-box;\"\u003e    Visualize complex multi-variable datasets\u003cbr style=\"box-sizing: border-box;\"\u003e    Train a decision tree machine learning algorithm\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eAbout the reader\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003eFor readers who know the basics of Python. No prior data science or machine learning skills required.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eAbout the Author\u003c\/strong\u003e\u003c\/span\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cspan class=\"a-text-bold\" style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-weight:\u003eLeonard Apeltsin\u003c\/span\u003e\u003cspan style=\"box-sizing: border-box; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse.\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eCASE STUDY 1 FINDING THE WINNING STRATEGY IN A CARD GAME\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e1 Computing probabilities using Python\u003cbr style=\"box-sizing: border-box;\"\u003e2 Plotting probabilities using Matplotlib\u003cbr style=\"box-sizing: border-box;\"\u003e3 Running random simulations in NumPy\u003cbr style=\"box-sizing: border-box;\"\u003e4 Case study 1 solution\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eCASE STUDY 2 ASSESSING ONLINE AD CLICKS FOR SIGNIFICANCE\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e5 Basic probability and statistical analysis using SciPy\u003cbr style=\"box-sizing: border-box;\"\u003e6 Making predictions using the central limit theorem and SciPy\u003cbr style=\"box-sizing: border-box;\"\u003e7 Statistical hypothesis testing\u003cbr style=\"box-sizing: border-box;\"\u003e8 Analyzing tables using Pandas\u003cbr style=\"box-sizing: border-box;\"\u003e9 Case study 2 solution\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eCASE STUDY 3 TRACKING DISEASE OUTBREAKS USING NEWS HEADLINES\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e10 Clustering data into groups\u003cbr style=\"box-sizing: border-box;\"\u003e11 Geographic location visualization and analysis\u003cbr style=\"box-sizing: border-box;\"\u003e12 Case study 3 solution\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eCASE STUDY 4 USING ONLINE JOB POSTINGS TO IMPROVE YOUR DATA SCIENCE RESUME\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e13 Measuring text similarities\u003cbr style=\"box-sizing: border-box;\"\u003e14 Dimension reduction of matrix data\u003cbr style=\"box-sizing: border-box;\"\u003e15 NLP analysis of large text datasets\u003cbr style=\"box-sizing: border-box;\"\u003e16 Extracting text from web pages\u003cbr style=\"box-sizing: border-box;\"\u003e17 Case study 4 solution\u003cbr style=\"box-sizing: border-box;\"\u003e\u003cstrong\u003eCASE STUDY 5 PREDICTING FUTURE FRIENDSHIPS FROM SOCIAL NETWORK DATA\u003c\/strong\u003e\u003cbr style=\"box-sizing: border-box;\"\u003e18 An introduction to graph theory and network analysis\u003cbr style=\"box-sizing: border-box;\"\u003e19 Dynamic graph theory techniques for node ranking and social network analysis\u003cbr style=\"box-sizing: border-box;\"\u003e20 Network-driven supervised machine learning\u003cbr style=\"box-sizing: border-box;\"\u003e21 Training linear classifiers with logistic regression\u003cbr style=\"box-sizing: border-box;\"\u003e22 Training nonlinear classifiers with decision tree techniques\u003cbr style=\"box-sizing: border-box;\"\u003e23 Case study 5 solution\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e \u003cb\u003eeBook License\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eEnd-User Warranty and License Agreement\u003c\/p\u003e\u003cp\u003e1. Grant of License\u003c\/p\u003e\u003cp\u003eManning has authorized the download by you of an unrestricted number of copies of the electronic book (ebook) in any of the available formats. Manning grants you a nonexclusive, nontransferable license to use the ebook according to the terms and conditions herein. This License Agreement permits you to install the ebook on any and all your devices for your personal use only.\u003c\/p\u003e\u003cp\u003e2. Restrictions\u003c\/p\u003e\u003cp\u003eYou shall not: (1) share, resell, rent, assign, timeshare, distribute, or transfer all or part of the ebook or any rights granted hereunder to any other person; (2) duplicate the ebook, except for a single backup or archival copy; (3) remove any proprietary notices, labels, or marks from the ebook; (4) transfer or sublicense title to the ebook to any other party.\u003c\/p\u003e\u003cp\u003e3. 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Limited Warranty\u003c\/p\u003e\u003cp\u003eManning warrants that the ebook files, a copy of which you are authorized to download, are free from defects in the operational sense that they can be read by a PDF Reader or ePub reader, or other. EXCEPT FOR THIS EXPRESS LIMITED WARRANTY, MANNING MAKES AND YOU RECEIVE NO WARRANTIES, EXPRESS, IMPLIED, STATUTORY OR IN ANY COMMUNICATION WITH YOU, AND MANNING SPECIFICALLY DISCLAIMS ANY OTHER WARRANTY INCLUDING THE IMPLIED WARRANTY OF MERCHANTABILITY OR FITNESS OR A PARTICULAR PURPOSE. MANNING DOES NOT WARRANT THAT THE OPERATION OF THE EBOOK WILL BE UNINTERRUPTED OR ERROR FREE. If the ebook was purchased in the United States, the above exclusions may not apply to you as some states do not allow the exclusion of implied warranties. In addition to the above warranty rights, you may also have other rights that vary from state to state.\u003c\/p\u003e\u003cp\u003e6. 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This Agreement is governed by the laws of the State of New York.\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e","brand":"Manning Publications","offers":[{"title":"Paperback","offer_id":50506260774982,"sku":"9781617296253","price":3950.0,"currency_code":"INR","in_stock":true},{"title":"E-Book","offer_id":50506260807750,"sku":"9781617296253-2","price":4333.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/71Zb98PMnML.jpg?v=1790324485","url":"https:\/\/cb-india.com\/products\/data-science-bookcamp-pfive-real-world-python-projects-paperback-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}