課程大綱： Machine Learning Concepts for Entrepreneurs and Managers培訓
Introduction to Neural Networks
Introduction to Applied Machine Learning
Statistical learning vs. Machine learning
Iteration and evaluation
Bias-Variance trade-off
Machine Learning with Python
Choice of libraries
Add-on tools
Machine learning Concepts and Applications
Regression
Linear regression
Generalizations and Nonlinearity
Use cases
Classification
Bayesian refresher
Naive Bayes
Logistic regression
K-Nearest neighbors
Use Cases
Cross-validation and Resampling
Cross-validation approaches
Bootstrap
Use Cases
Unsupervised Learning
K-means clustering
Examples
Challenges of unsupervised learning and beyond K-means
Short Introduction to NLP methods
word and sentence tokenization
text classification
sentiment analysis
spelling correction
information extraction
parsing
meaning extraction
question answering
Artificial Intelligence & Deep Learning
Technical Overview
R v/s Python
Caffe v/s Tensor Flow
Various Machine Learning Libraries
Industry Case Studies
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