Hidden Markov Models Courses and Certifications

NPTEL;  IIT Kharagpur

Pattern Recognition and Application

This course covers feature extraction techniques and the representation of patterns in feature space. Measure of similarity between two patterns. Statistical, nonparametric and neural network techniques for pattern recognition have been discussed in this…

• YouTube
• 1 day 13 hours
• On-Demand
• Free Video

Fundamentals of Dynamic Programming

388 ratings at LinkedIn Learning

Dynamic programming makes it possible to solve challenging problems efficiently. Learn what it is, how and when to apply it to your algorithms, and how it's used in applications.

• LinkedIn Learning
• 1 hour 26 minutes
• On-Demand
• Free Trial Available

Beijing Institute of Technology

Machine Learning and Knowledge Discovery

Master machine learning fundamentals through hands-on PyTorch implementation, covering neural networks, SVMs, deep learning architectures, and practical applications in robotics, computer vision, and text analysis.

• XuetangX
• On-Demand
• Free Online Course

Algorithms in Computational Biology and Sequence Analysis

Master computational biology algorithms and data structures for analyzing genomic datasets, from sequence alignment to evolutionary tree construction, with hands-on programming using real biological data like SARS-CoV2.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Beijing Institute of Technology

Machine Learning and Knowledge Discovery

Master machine learning fundamentals and advanced concepts through hands-on PyTorch implementation, covering neural networks, deep learning architectures, and practical applications in robotics and computer vision.

• XuetangX
• On-Demand
• Free Online Course

Beijing Institute of Technology

Digital Speech Signal Processing

Students can master the basic theory of digital speech signal processing and mathematical analysis and modeling method of sound object through this course.

• XuetangX
• On-Demand
• Free Online Course

Bioinformatics Course Lectures

Comprehensive bioinformatics lectures covering genomics, sequencing, evolution, statistics, alignment, phylogenetics, assembly, annotation, and genetic variation for aspiring bioinformaticians.

• YouTube
• 14 hours
• On-Demand
• Free Video

BioinformaticsDotCA

CBW's Machine Learning Workshops May 25-26, 2021

Comprehensive workshop on machine learning in bioinformatics, covering decision trees, neural networks, hidden Markov models, and practical applications using Keras and Scikit-Learn.

• YouTube
• 7 hours
• On-Demand
• Free Video

Serrano.Academy

Probability

Explore Bayes Theorem, Hidden Markov Models, Shannon Entropy, Naive Bayes classifier, Beta distribution, and Thompson sampling in this friendly introduction to key probability concepts.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

IEEE

Smoothed Analysis in Unsupervised Learning via Decoupling

Explore smoothed analysis in unsupervised learning, focusing on tensor decomposition, high-dimensional data, and robust subspace recovery. Gain insights into condition number bounds and perturbation techniques.

• YouTube
• 21 minutes
• On-Demand
• Conference Talk

Simons Institute

Recent Progress in High-Dimensional Learning

Explore recent advancements in high-dimensional learning, covering factor analysis, phylogenetic reconstruction, and hidden Markov models, with applications in genetics and machine learning.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Alan Turing Institute

Time Series Class - Part 1 - Dr Ioannis Papastathopoulos, University of Edinburgh

Learn fundamental concepts and advanced techniques for analyzing time series data, including ARMA models, state-space models, and neural networks for forecasting and inference.

• YouTube
• 1 hour 50 minutes
• On-Demand
• Free Video

Alan Turing Institute

Time Series Class - Part 1 - Dr. Ioannis Papastathopoulos, University of Edinburgh

Learn fundamental concepts and advanced techniques in time series analysis, including ARMA models, state-space models, and neural networks for forecasting and inference.

• YouTube
• 1 hour 51 minutes
• On-Demand
• Free Video

Alan Turing Institute

Time Series Class - Part 2 - Professor Chris Williams, University of Edinburgh

Explore time series analysis, from moving average models to advanced state-space techniques and recurrent neural networks. Gain practical skills in parameter estimation, forecasting, and applying models to real-world data.

• YouTube
• 53 minutes
• On-Demand
• Free Video

Alan Turing Institute

Data Science Applications - Environment/Ecology

Explore statistical modeling techniques for ecological data, focusing on hidden Markov models, Bayesian inference, and capture-recapture methods. Learn to analyze and interpret complex environmental datasets.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video