Data Science Fundamentals Part 2: Machine Learning and Statistical Analysis

If nothing else, by the end of this video course you will have analyzed a number of datasets from the wild, built a handful of applications, and applied machine learning algorithms in meaningful ways to get real results. And all along the way you learn the best practices and computational techniques used by professional data scientists. You get hands-on experience with the PyData ecosystem by manipulating and modeling data. You explore and transform data with the pandas library, perform statistical analysis with SciPy and NumPy, build regression models with statsmodels, and train machine learning algorithms with scikit-learn. All throughout the course you learn to test your assumptions and models by engaging in rigorous validation. Finally, you learn how to share your results through effective data visualization.

Code:https://github.com/hopelessoptimism/data-science-fundamentals
Resources: http://hopelessoptimism.com/data-science-fundamentals
Forum:https://gitter.im/data-science-fundamentals
Data: http://insideairbnb.com/get-the-data.html

Password/解压密码-0daydown

Download rapidgator

Download nitroflare

Download 百度云

你是VIP 1个月(1 month)赞助会员，