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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Author(s): AnkurAnkan, Abinash Panda
Publisher: Packt Publishing
Published: September 2018
Format(s): Online
File size: –
Number of pages: 178
Download / View Link(s): This offer has ended.
Free as of 09/10/2022.
Publisher: Packt Publishing
Published: September 2018
Format(s): Online
File size: –
Number of pages: 178
Download / View Link(s): This offer has ended.
Free as of 09/10/2022.