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115 lines
4.6 KiB
115 lines
4.6 KiB
11 months ago
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<title>Julio Biason .Me 4.3</title>
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<link rel="stylesheet" href="https://blog.juliobiason.me/print.css" media="print">
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<link rel="stylesheet" href="https://blog.juliobiason.me/poole.css">
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</head>
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<body class=" ">
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<div class="sidebar">
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<div class="container sidebar-sticky">
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<div class="sidebar-about">
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<a href="https://blog.juliobiason.me"><h1>Julio Biason .Me 4.3</h1></a>
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<p class="lead">Old school dev living in a 2.0 dev world</p>
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</div>
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<ul class="sidebar-nav">
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<li class="sidebar-nav-item"><a href="/">English</a></li>
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<li class="sidebar-nav-item"><a href="/pt">Português</a></li>
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<li class="sidebar-nav-item"><a href="/tags">Tags (EN)</a></li>
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<li class="sidebar-nav-item"><a href="/pt/tags">Tags (PT)</a></li>
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</ul>
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<div class="content container">
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<div class="post">
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<h1 class="post-title">Python Data Science Essentials - Learn the fundamentals of Data Science with Python - Alberto Boschetti</h1>
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<span class="post-date">
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2016-12-16
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<a href="https://blog.juliobiason.me/tags/books/">#books</a>
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<a href="https://blog.juliobiason.me/tags/alberto-boschetti/">#alberto boschetti</a>
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<a href="https://blog.juliobiason.me/tags/reviews/">#reviews</a>
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<a href="https://blog.juliobiason.me/tags/python/">#python</a>
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<a href="https://blog.juliobiason.me/tags/data-science/">#data science</a>
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<a href="https://blog.juliobiason.me/tags/it/">#it</a>
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<a href="https://blog.juliobiason.me/tags/stars-2/">#stars:2</a>
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<a href="https://blog.juliobiason.me/tags/published-2015/">#published:2015</a>
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</span>
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<p><a href="https://www.goodreads.com/book/show/25527772-python-data-science-essentials---learn-the-fundamentals-of-data-science">GoodReads Summary</a>:
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Key Features Quickly get familiar with data science using Python Save time -
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and effort - with all the essential tools explained Create effective data
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science projects and avoid common pitfalls with the help of examples and hints
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dictated by experience Book Description</p>
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<span id="continue-reading"></span><div>
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★★☆☆☆
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</div>
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<p>It's hard to explain this book, mostly because it's hard to get to whom it is
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targeted.</p>
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<p>Is it targeted to people that already know Machine Learning and want to learn
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Python? No, the book goes into lengths into some algorithms and has "easy to
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write, but not quite right" code to do so.</p>
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<p>Is it targeted to people that know Python but want to learn Machine Learning?
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No; even if some algorithms are explained in length, some aren't and there is
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very little "you use this when you have data like that" explanations.
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Actually, there is very little explanation on where an algorithm should be
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used.</p>
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<p>Is it targeted to people that don't know Python and don't know Machine
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Learning and want to learn but? This is the gray area of the book: Again, the
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code is pretty simple and does not follow Python coding standards and the ML
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part is really shallow on the "when" and "why" sections.</p>
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<p>In the end, the book is simply an extended version of Scikit-Learn manual --
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and I even have doubts if the manual isn't better because it explains when an
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algorithm should be used.</p>
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</html>
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