Data Science From Scratch by Cooper, Steven -- Read -- Imperial Library of Trantor

Index

Preface Introduction Data Science and its Importance What is it Exactly? Why It Matters What You Need The Advantages to Data Science Data Science and Big Data Key Difference Between Data Science and Big Data Data Scientists The Process of Data Science Responsibilities of a Data Scientist Qualifications of Data Scientists Would You Be a Good Data Scientist? The Importance of Hacking The Importance of Coding Writing Production-Level Code Python SQL R SAS Java Scala Julia How to Work with Data Data Cleaning and Munging Data Manipulation Data Rescaling Python Installing Python Python Libraries and Data Structures Conditional and Iteration Constructs Python Libraries Exploratory Analysis with Pandas Creating a Predictive Model Machine Learning and Analytics Linear Algebra Vectors Matrices Statistics Discrete Vs. Continuous Statistical Distributions PDFs and CDFs Testing Data Science Models and Accuracy Analysis Some Algorithms and Theorems Decision Trees Neural Networks Scalable Data Processing Batch Processing Systems Apache Hadoop Stream Processing Systems Apache Storm Apache Samza Hybrid Processing Systems Apache Spark Apache Flink Data Science Applications Conclusion About the author References Sign up for Steven Cooper's Mailing List Also By Steven Cooper

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