Data Science Solutions with Python : Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn By Tshepo Chris Nokeri
Material type: TextPublication details: Apress, c2022.Edition: 1Description: i-xvi+119PISBN:- 9781484283509
- 1 006.31 NOK-D
Item type | Current library | Home library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | Dept. of Computational Biology and Bioinformatics | Dept. of Computational Biology and Bioinformatics | 006.31 NOK-D (Browse shelf(Opens below)) | Available | DCB4164 |
Chapter 1: Understanding Machine Learning and Deep Learning
Chapter 2: Big Data Frameworks and ML and DL Frameworks
Chapter 3: The Parametric Method Linear Regression
Chapter 4: Survival Regression Analysis.-Chapter 5:The Non-Parametric Method - Classification
Chapter 6:Tree-based Modelling and Gradient Boosting
Chapter 7: Artificial Neural Networks
Chapter 8: Cluster Analysis using K-Means
Chapter 9: Dimension Reduction Principal Components Analysis
Chapter 10: Automated Machine Learning
Apply supervised and unsupervised learning to solve practical and real-world big data problems
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