Study Materials

1. "Data Mining and Data Wear Housing" by Jaiwei Han, Micheline Kamber and Jian Pie. (pdf)
2. "Pattern Recognition and Machine Learning" by Christopher Bishop. (pdf)
3. "Pattern Classification" by Richard O. Duda, David G. Stork, Peter E.Hart. (pdf)
4. "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, Jerome Friedman. (pdf)
5. "Learning From Data (a short course)" by Yaser S. Abu-Mosta, Malik Magdon-Ismail, Hsuan-Tien Lin. (pdf)
6. "Machine Learning" by Tom M. Mitchell (pdf)
7. "Introduction to Machine Learning" by Ethem Alpaydın. (pdf)
8. "Neural Networks and Learning Machines" by Simon Haykin. (pdf)
9. "An Introduction to Information Retrieval" by Christopher D. Manning Prabhakar Raghavan Hinrich Schütze. (pdf)
10. Kernel methods for Pattern Classification by John Shawe-Taylor, Nello Cristianini .(pdf)
11. Digital Image Processing by Rafael C. Gonzalez & Richard E. Woods. (pdf)

• Online Graphing Calculator. (click here)
• A visual Introduction to Machine Learning - Decision Tree. (click here)
• A neural Network Playground. (click here)
• ML Training/Testing/Loss Curves & their growth.(click here)

• Machine Learning Datasets from School of Computing,University of Eastern Finland. (Click here)
• UCI Machine learning Repository (Click here)
• Pen Based Recognition of Handwritten Digits Dataset. (Click here)
• Irish Plants Dataset. (Click here)
• MNIST Dataset. (Click Here)
• Face Dataset from AT & T Laboratory, Cambridge. (Click here)

References for Various Libraries and Toolkits.