Data science from scratch first principles with Python
With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Sebastopol (CA)
O'Reilly Media
2019.
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| Edition: | Second edition. |
| Subjects: | |
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Table of Contents:
- Introduction
- A crash course in Python
- Visualizing data
- Linear algebra
- Statistics
- Probability
- Hypothesis and inference
- Gradient descent
- Getting data
- Working with data
- Machine learning
- k-Nearest neighbors
- Naive bayes
- Simple linear regression
- Multiple regression
- Logistic regression
- Decision trees
- Neural networks
- Deep learning
- Clustering
- Natural language processing
- Network analysis
- Recommender systems
- Databases and SQL
- MapReduce
- Data ethics
- Go forth and do data science