Machine Learning in Action
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BookPal × TalezoMachine Learning in Action
Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.
About the Book
A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many.
Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification.
Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful.
What's Inside
- A no-nonsense introduction
- Examples showing common ML tasks
- Everyday data analysis
- Implementing classic algorithms like Apriori and Adaboos
- PART 1 CLASSIFICATION
- Machine learning basics
- Classifying with k-Nearest Neighbors
- Splitting datasets one feature at a time: decision trees
- Classifying with probability theory: naïve Bayes
- Logistic regression
- Support vector machines
- Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION
- Predicting numeric values: regression
- Tree-based regression PART 3 UNSUPERVISED LEARNING
- Grouping unlabeled items using k-means clustering
- Association analysis with the Apriori algorithm
- Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS
- Using principal component analysis to simplify data
- Simplifying data with the singular value decomposition
- Big data and MapReduce
Details
- Publisher
- Manning
- Author
- Peter Harrington
- Format
- Paperback
- Published
- Apr 19, 2012
- ISBN-13
- 9781617290183
- ISBN-10
- 1617290181
- Pages
- 384
- Carton quantity
- 10 copies
Machine Learning in Action for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 99 | $38.24 | 15% off list |
| 100 – 249 | $37.79 | 16% off list |
| 250 – 499 | $37.34 | 17% off list |
| 500 – 999 | $36.89 | 18% off list |
| 1,000+ | $35.99 | 20% off list |
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Volume pricing applies automatically in your cart, with no code needed. Price per copy: 25 to 99 copies, $38.24 (15% off list); 100 to 249 copies, $37.79 (16% off list); 250 to 499 copies, $37.34 (17% off list); 500 to 999 copies, $36.89 (18% off list); 1,000+ copies, $35.99 (20% off list). Need a different quantity, or a quote to forward for approval? Ask a specialist and we will confirm pricing before you pay.
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