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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
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