{"product_id":"data-science-bookcamp","title":"Data Science Bookcamp","description":"\u003cdiv class=\"product-section\" style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003cdiv class=\"description-body\" style=\"text-align: left;margin-bottom: 21.0px;\"\u003e   Learn data science with Python by building five real-world projects! In   \u003cspan\u003e \u003c\/span\u003e   \u003ci style=\"\"\u003eData Science Bookcamp\u003c\/i\u003e   \u003cspan\u003e \u003c\/span\u003eyou’ll test and build your knowledge of Python and learn to handle the kind of open-ended problems that professional data scientists work on daily. 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.  \u003c\/div\u003e \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the technology\u003c\/h2\u003eIn real-world practice, data scientists create innovative solutions to novel open ended problems. Easy to learn and use, the Python language has become the de facto language for data science amongst researchers, developers, and business users. But knowing a few basic algorithms is not enough to tackle a vague and thorny problem. It takes relentless practice at cracking difficult data tasks to achieve mastery in the field. That’s just what this book delivers. \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the book\u003c\/h2\u003e  \u003ci style=\"\"\u003eData Science Bookcamp\u003c\/i\u003e  \u003cspan\u003e \u003c\/span\u003eis a comprehensive set of challenging projects carefully designed to grow your data science skills from novice to master. Veteran data scientist Leonard Apeltsin sets five increasingly difficult exercises that test your abilities against the kind of problems you’d encounter in the real world. As you solve each challenge, you’ll acquire and expand the data science and Python skills you’ll use as a professional data scientist. Ranging from text processing to machine learning, each project comes complete with a unique downloadable data set and a fully-explained step-by-step solution. Because these projects come from Dr. Apeltsin’s vast experience, each solution highlights the most likely failure points along with practical advice for getting past unexpected pitfalls. When you wrap up these five awesome exercises, you’ll have a diverse relevant skill set that’s transferable to working in industry. \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e    \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003ewhat''s inside\u003c\/h2\u003e   \u003cul style=\"margin-top: 0.0px;margin-bottom: 10.5px;\"\u003e    \u003cli style=\"\"\u003eFive in-depth Python exercises with full downloadable data sets\u003c\/li\u003e    \u003cli style=\"\"\u003eWeb scraping for text and images\u003c\/li\u003e    \u003cli style=\"\"\u003eOrganise datasets with clustering algorithms\u003c\/li\u003e    \u003cli style=\"\"\u003eVisualize complex multi-variable datasets\u003c\/li\u003e    \u003cli style=\"\"\u003eTrain a decision tree machine learning algorithm\u003c\/li\u003e   \u003c\/ul\u003e  \u003c\/div\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the reader\u003c\/h2\u003eFor readers who know the basics of Python. No prior data science or machine learning skills required.  \u003c\/div\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the author\u003c\/h2\u003e   \u003cb style=\"font-weight: bold;\"\u003eLeonard Apeltsin\u003c\/b\u003e   \u003cspan\u003e \u003c\/span\u003eis a senior data scientist and engineering lead at Primer AI, a startup that specializes in using advanced Natural Language Processing techniques to extract insight from terabytes of unstructured text data. His PhD research focused on bioinformatics that required analyzing millions of sequenced DNA patterns to uncover genetic links in deadly diseases.  \u003c\/div\u003e \u003c\/div\u003e","brand":"MediaPlace","offers":[{"title":"Default Title","offer_id":57314725298558,"sku":"NW9781617296253","price":50.95,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1379\/1261\/files\/9781617296253.jpg?v=1778714191","url":"https:\/\/mediaplace.com\/en-eu\/products\/data-science-bookcamp","provider":"MediaPlace","version":"1.0","type":"link"}