Data Science and Machine Learning with Python - Hands On!Frank Kane
了解如何使用Python、Pandas、NumPy、Matplotlib、Seaborn、Data Wrangling、Learnbuild模型、训练和部署模型。 你将学到什么 理解数据科学的基本概念。 认识到数据科学的应用和行业影响。 熟练使用Python和R编程语言进行数据分析。 利用重要的数据科学库,如Pandas、NumPy、Matplotlib和Seaborn。 安装Python并在Windows和macOS上...
Written by a data scientist with decades of practical experience on some of the most challenging datasets, this book caters to both novices and professionals working in the fields of data science a...
This course is designed for anyone eager to embark on a journey into data science or enhance their existing skills Aspiring Data Scientists Individuals looking to break into the field and build a strong foundation in data analysis and machine learning. ...
Python considerably streamlines the process. Goals Beginners who are interested in Machine Learning using Python Learn fundamentals of machine learning and data science using Python Develop the skills you need to apply machine learning and data science to real-world problems Prepare for a career in ...
Data Science with Python: Machine Learning This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. The five sessions cover: simple and multiple Linear regressions; classification methods including ...
Complete Python Course: Data Science, Artificial Intelligence, and Machine Learning from basics to advanced What you’ll learn: Learn the basics of Data Science, Artificial Intelligence, and Machine Learning Understand and implement the Python Environment Setup ...
Manohar Swamynathan is a data science practitioner and an avid programmer, with over 14+ years of experience in various data science related areas that include data warehousing, Business Intelligence (BI), analytical tool development, ad-hoc analysis, predictive modeling, data science product developme...
Complete resource to prepare for successful Data Science career. Go from Beginner to Data Science Expert, become Fundamentally Strong in ML.
Introduction toMachine Learning (1) Data Science Languages: Python, R, SQL, JavaScript (D3.js) Mathematics: Advanced algebra, linear algebra, probability, Bayesian statistics, calculus (2) Machine Learning (ML) Techniques:Regression, classification, density estimation, dimension reduction, clustering Ty...