Python for data scientists scikitlearn specializationscikitlearn, also known as sklearn, is a free, opensource machine learning ml library used for the python language. In february 2010, this library was first made public. And in less than three years, it became one of the most popular machine learning libraries on github.Scikitlearn is the best place to start for access to easytouse, topnotch implementations of popular algorithms. This library speeds up the development of ml models.The main features of the scikitlearn library are regression, classification, and clustering algorithms random forests, kmeans, gradient boosting, dbscan, and support vector machines . The scikitlearn library also integrates well with other python libraries, such as numpy, pandas, ipython, scipy, sympy, and matplotlib, to fulfill different tasks.Python for data scientists scikitlearn specialization presents you with a handson, simple approach to learn scikitlearn fast.How is this book different.Most python books assume you know how to code using pandas, numpy, and matplotlib. But this book does not. The author spends a lot of time teaching you how actually write the simplest codes in python to achieve machine learning models.Indepth coverage of the scikitlearn library starts from the third chapter itself. Jumping straight to scikitlearn makes it easy for you to follow along. The other advantage is jupyter notebook is used to write and explain the code right through this book.You can access the datasets used in this book easily by downloading them at runtime. You can also access them through the datasets folder in the sharepoint and github repositories.You also get to work on three handson miniprojects spam email detection with scikitlearnimdb movies sentimental analysisimage classification with scikitlearnthe scripts, graphs, and images in the book are clear and provide easytounderstand visuals to the text description. If youre new to data science, you will find this book a great option for selfstudy. Overall, you can count on this learning by doing book to help you accomplish your data science career goals faster.The topics covered include introduction to scikitlearn and other machine learning librariesenvironment setup and python crash coursedata preprocessing with scikitlearnfeature selection with python scikitlearn librarysolving regression problems in machine learning using sklearn librarysolving classification problems in machine learning using sklearn libraryclustering data with scikitlearn librarydimensionality reduction with pca and lda using sklearnselecting best models with scikitlearnnatural language processing with scikitlearnimage classification with scikitlearnhit the buy now button and start your data science learning journey.