Search results for Markov Chain Monte Carlo

Found 24 documents, 5922 searched:

• Practical Markov Chain Monte Carlo

  This is a slightly more intricate example of MCMC, compared to many with a fairly simple model, a single predictor (maybe two), and not much else, which highlights a couple of issues and tricks worth noting for a handwritten implementation.

  https://www.kdnuggets.com/2020/06/practical-markov-chain-monte-carlo.html

• Monte Carlo integration in Python">Monte Carlo integration in Python

  A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python?

  https://www.kdnuggets.com/2020/12/monte-carlo-integration-python.html

• 5 Free Books to Master Statistics for Data Science

  Statistics is a must-have skill for data science. And here are 5 free books that’ll help you learn all the statistics you need as a data professional.

  https://www.kdnuggets.com/5-free-books-to-master-statistics-for-data-science

• Neural Networks from a Bayesian Perspective

  This article looks at neural networks from a Bayesian perspective.

  https://www.kdnuggets.com/2021/11/neural-networks-bayesian-perspective.html

• My Data Science Online Learning Journey on Coursera

  Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.

  https://www.kdnuggets.com/2020/11/data-science-online-learning-journey-coursera.html

• The Best Free Data Science eBooks: 2020 Update">The Best Free Data Science eBooks: 2020 Update

  The author has updated their list of best free data science books for 2020. Read on to see what books you should grab.

  https://www.kdnuggets.com/2020/09/best-free-data-science-ebooks-2020-update.html

• Essential Resources to Learn Bayesian Statistics">Essential Resources to Learn Bayesian Statistics

  If you are interesting in becoming better at statistics and machine learning, then some time should be invested in diving deeper into Bayesian Statistics. While the topic is more advanced, applying these fundamentals to your work will advance your understanding and success as an ML expert.

  https://www.kdnuggets.com/2020/07/essential-resources-learn-bayesian-statistics.html

• Outbreak Analytics: Data Science Strategies for a Novel Problem

  You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?

  https://www.kdnuggets.com/2020/04/outbreak-analytics-data-science-novel-problem.html

• NLP Year in Review — 2019

  In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.

  https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html

• Spatio-Temporal Statistics: A Primer

  Marketing scientist Kevin Gray asks University of Missouri Professor Chris Wikle about Spatio-Temporal Statistics and how it can be used in science and business.

  https://www.kdnuggets.com/2019/04/spatio-temporal-statistics-primer.html

• Top 20 Python AI and Machine Learning Open Source Projects">Top 20 Python AI and Machine Learning Open Source Projects

  We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.

  https://www.kdnuggets.com/2018/02/top-20-python-ai-machine-learning-open-source-projects.html

• 5 Machine Learning Projects You Should Not Overlook">5 Machine Learning Projects You Should Not Overlook

  It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out!

  https://www.kdnuggets.com/2018/02/5-machine-learning-projects-overlook-feb-2018.html

• The 10 Statistical Techniques Data Scientists Need to Master">The 10 Statistical Techniques Data Scientists Need to Master

  The author presents 10 statistical techniques which a data scientist needs to master. Build up your toolbox of data science tools by having a look at this great overview post.

  https://www.kdnuggets.com/2017/11/10-statistical-techniques-data-scientists-need-master.html

• Top 20 Python Machine Learning Open Source Projects, updated">Top 20 Python Machine Learning Open Source Projects, updated

  Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.

  https://www.kdnuggets.com/2016/11/top-20-python-machine-learning-open-source-updated.html

• A simple approach to anomaly detection in periodic big data streams

  We describe a simple and scaling algorithm that can detect rare and potentially irregular behavior in a time series with periodic patterns. It performs similarly to Twitter's more complex approach.

  https://www.kdnuggets.com/2016/08/anomaly-detection-periodic-big-data-streams.html

• Top 30 Social Network Analysis and Visualization Tools

  We review major tools and packages for Social Network Analysis and visualization, which have wide applications including biology, finance, sociology, network theory, and many other domains.

  https://www.kdnuggets.com/2015/06/top-30-social-network-analysis-visualization-tools.html

• Most Viewed Machine Learning Talks at Videolectures

  Discover lectures from a variety of summer schools and conference tutorials on machine learning in this list of the top lectures on the subject from videolectures.net.

  https://www.kdnuggets.com/2014/09/most-viewed-machine-learning-talks-videolectures.html

• Top 10 Big Ideas in Harvard Statistics 110 Class

  The Big Ideas in Statistics include: Conditioning (the soul of statistics), Random variables and random vectors, Stories, Symmetry, Linearity of expectation, LOTUS, Variance, covariance, and correlation.

  https://www.kdnuggets.com/2013/12/top-10-big-ideas-harvard-statistics-110-class.html

• The Ultimate Guide to Acing Coding Interviews for Data Scientists">The Ultimate Guide to Acing Coding Interviews for Data Scientists

  This article covers understanding the 4 types of coding interview questions and preparing for them effectively.

  https://www.kdnuggets.com/2021/03/ultimate-guide-acing-coding-interviews-data-scientists.html

• Statistics with Julia: The Free eBook">Statistics with Julia: The Free eBook

  This free eBook is a draft copy of the upcoming Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence. Interested in learning Julia for data science? This might be the best intro out there.

  https://www.kdnuggets.com/2020/09/statistics-julia-free-ebook.html

• Free Mathematics Courses for Data Science & Machine Learning">Free Mathematics Courses for Data Science & Machine Learning

  It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.

  https://www.kdnuggets.com/2020/02/free-mathematics-courses-data-science-machine-learning.html

• Detecting stationarity in time series data

  Explore how to determine if your time series data is generated by a stationary process and how to handle the necessary assumptions and potential interpretations of your result.

  https://www.kdnuggets.com/2019/08/stationarity-time-series-data.html

• Applied Statistics Is A Way Of Thinking, Not Just A Toolbox

  The choice of tools in applied statistics is driven by the objective, the structure of the data, and the nature of the uncertainty in the numbers, whereas in academic statistics its driven by publishing or teaching. Here we provide some of common statistical tools and the overlapping genealogy.

  https://www.kdnuggets.com/2015/05/applied-statistics-thinking-not-toolbox.html

• Interview: Pedro Domingos: the Master Algorithm, new type of Deep Learning, great advice for young researchers

  Top researcher Pedro Domingos on useful maxims for Data Mining, Machine Learning as the Master Algorithm, new type of Deep Learning called sum-product networks, Big Data and startups, and great advice to young researchers.

  https://www.kdnuggets.com/2014/08/interview-pedro-domingos-master-algorithm-new-deep-learning.html