Hands-On Markov Models with Python

Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. (Limited-time offer)

Table of Contents

• Section 1: The Rationale of Machine Learning and the Usage of TensorFlow.js
• Machine Learning for the Web
• Importing Pretrained Models into TensorFlow.js
• TensorFlow.js Ecosystem
• Section 2: Real-World Applications of TensorFlow.js
• Polynomial Regression
• Classification with Logistic Regression
• Unsupervised Learning
• Sequential Data Analysis
• Dimensionality Reduction
• Solving the Markov Decision Process
• Section 3: Productionizing Machine Learning Applications with TensorFlow.js
• Deploying Machine Learning Applications
• Tuning Applications to Achieve High Performance
• Future Work Around TensorFlow.js

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