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Index
Introduction Chapter 1: Introduction to machine learning Chapter 2: Types of machine learning Machine learning under supervision Machine learning without supervision Semi-supervised machine learning Strengthening machine learning Importance of machine learning Automation of repetitive learning and information disclosure Core concepts of machine learning Representation Evaluation Optimization Statistical learning framework Forecast and inference Parametric and non-parametric techniques Predictions Accuracy and model interpretability Assess model accuracy Bias and deviation The interaction between bias and variance Chapter 3 : Machine learning algorithms Regression Classification Generate predictions using logistic regression Types of "Naive Bayes classification" Chapter 4 : Neural network learning models Components of ANNs Hyperparameter of ANN Neural network training with data pipeline 1. Problem definition 2. Data recording 3. Data preparation 4. Separation of data 5. Model training Neural network training approaches Guided training Uncontrolled training 6. Candidate model evaluation 7. Model implementation 6. Candidate model evaluation 7. Model implementation 9. Performance monitoring Applications of neural network models Chapter 5 : Learning through uniform convergence Impact of uniform convergence on learnability Learnability without uniform convergence Chapter 6 : Data Science Lifecycle and Technologies Data science life cycle Definition of a data science life cycle Standardized project structure Infrastructure and resources for data science projects Project execution tools and utilities Phase I - Business understanding Products to be delivered in this phase Phase II - Data acquisition and understanding Data recording Data exploration Set up a data pipeline Products to be delivered in this phase Stage III - Modeling Products to be delivered in this phase Stage IV implementation Operationalize the model Products to be delivered in this phase Phase V - Customer acceptance Products to be delivered in this phase Importance of Data Science Data science strategies Artificial intelligence Chapter 7 : Business Intelligence vs. Data Science Data mining Data Mining Trends Increased computer speed Language standardization Scientific mining Web mining Data Mining Tools RapidMiner Mahout MicroStrategy Conclusion
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