Amplie sua biblioteca! Confira a lista abaixo:
- An Introduction to Statistical Learning: with Applications in R
- Data Science for Business: What you need to know about data mining and data-analytic thinking
- Modeling With Data
- Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners
- Data Mining: Practical Machine Learning Tools and Techniques
- Machine Learning – Wikipedia Guide
- Data Mining and Analysis: Fundamental Concepts and Algorithms
- Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
- Probabilistic Programming & Bayesian Methods for Hackers
- Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
- Inductive Logic Programming Techniques and Applications
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
- An Introduction to Data Science
- Mining of Massive Datasets
- A Programmer’s Guide to Data Mining
- Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery
- Reinforcement Learning: An introduction
- Pattern Recognition and Machine Learning (Information Science and Statistics)
- Machine Learning, Neural and Statistical Classification
- Information Theory, Inference, and Learning Algorithms
- Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
- Introduction to Machine Learning
- Data Mining and Business Analytics with R
- Machine Learning
- Think Bayes, Bayesian Statistics Made Simple
- Bayesian Reasoning and Machine Learning
- Gaussian Processes for Machine Learning
Recomendamos iniciar com o 22, 23, 13 e 8, em qualquer ordem.
Um abraço e até o próximo post!
Leandro
ResponderExcluirExcelente dicas. Os temas são muito interessantes.
Vou iniciar pelo 23, mas o 3 também chamou muito a atenção.
Valeu!!!
Olá Helder, obrigado pela visita! Ainda não li o 3, mas vou dar uma olhada agora que você falou. Abraço!
Excluir