Joel Grus
Auteur van Data Science from Scratch: First Principles with Python
Over de Auteur
Joel Grus is a software engineer at Google. Before that, he worked as a data scientist at multiple startups. He lives in Seattle, where he regularly attends data science happy hours. He blogs infrequently at joelgrus.com and tweets all day long at@joelgrus.
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Data Science from Scratch door Joel Grus
I read this prior to beginning an MSc in Data Science and found it to be a great introduction to data science, starting out with the very basics before moving into more general ML techniques and finishing up with some of the more complex topics such as MapReduce. Not an in-depth textbook by any means, but I do not think that is the purpose of this book, moreover to give the reader a well-rounded idea of the field.
This is a very basic into topics in statistics and machine learning built around functioning code to perform (some of!) the tasks and algorithms discussed.
As an introduction it seemed very solid. I was looking for something a little more in depth, so this was not really the book I was looking for. What am I looking for? Something that bridges between a working knowledge of e.g. some methods in scikit learn to e.g. coding those methods, from scratch. Gradient descent and PCA are covered, but the book stops precisely at 'more interesting'/complex methods e.g. ridge regression/Lasso, and never even touches on e.g. ICA.
So, 3-ish stars for me. Maybe 4 stars if you are getting your feet wet for the first time.… (meer)
As an introduction it seemed very solid. I was looking for something a little more in depth, so this was not really the book I was looking for. What am I looking for? Something that bridges between a working knowledge of e.g. some methods in scikit learn to e.g. coding those methods, from scratch. Gradient descent and PCA are covered, but the book stops precisely at 'more interesting'/complex methods e.g. ridge regression/Lasso, and never even touches on e.g. ICA.
So, 3-ish stars for me. Maybe 4 stars if you are getting your feet wet for the first time.… (meer)
Great summary overview of both Python and statistical concepts and techniques.
As bibliotecas, estruturas, módulos e kits de ferramentas do data science são ótimas para desempenhá-lo mas, também, são uma ótima forma de mergulhar na disciplina sem ter, de fato, que entender data science. Neste livro, você aprenderá como os algoritmos e as ferramentas mais essenciais de data science funcionam ao implementá-los do zero.Se você tiver aptidão para matemática e alguma habilidade para programação, o autor Joel Grus lhe ajudará a se sentir confortável com matemática e estatística nos fundamentos de data science. Você precisará iniciar como um cientista de dados com habilidades de hackers. Atualmente, a grande massa de dados contém respostas para perguntas que ninguém nunca pensou em perguntar. Este guia fornece o conhecimento para desenterrar tais respostas.Obtenha um curso intensivo em Python;Aprenda o básico de álgebra linear, estatística e probabilidade ― e entenda como e quando eles são usados em data science;Colete, explore, limpe, mude e manipule dados;Vá fundo nos princípios do aprendizado de máquina;Implemente modelos como k-vizinhos mais próximos, Naive Bayes, regressão logística e linear, árvores de decisão, redes neurais e agrupamentos;Explore sistemas recomendados, processamento de linguagem natural, análise de rede, MapReduce e bases de dados. DEPOIMENTO:“Joel lhe leva em uma jornada desde a curiosidade sobre dados até a completa compreensão de algoritmos que todo cientista de dados deveria ter.”―Rohit Sivaprasad, Cientista de Dados na Soylent… (meer)
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- 3