- Neural Networks from a Bayesian Perspective - Nov 3, 2021.
This article looks at neural networks from a Bayesian perspective.
Bayesian, Neural Networks
- Bayesian Hyperparameter Optimization with tune-sklearn in PyCaret - Mar 5, 2021.
PyCaret, a low code Python ML library, offers several ways to tune the hyper-parameters of a created model. In this post, I'd like to show how Ray Tune is integrated with PyCaret, and how easy it is to leverage its algorithms and distributed computing to achieve results superior to default random search method.
Bayesian, Hyperparameter, Machine Learning, Optimization, PyCaret, Python, scikit-learn
- Facebook Uses Bayesian Optimization to Conduct Better Experiments in Machine Learning Models - Aug 10, 2020.
A research from Facebook proposes a Beyasian optimization method to run A/B tests in machine learning models.
Bayesian, Facebook, Machine Learning, Modeling, Optimization
- KDnuggets™ News 20:n29, Jul 29: Easy Guide To Data Preprocessing In Python; Building a better Spark UI; Computational Algebra for Coders: The Free Course - Jul 29, 2020.
An easy guide to data pre-processing in Python; Monitoring Apache Spark with a better Spark UI; Computational Linear Algebra for Coders: the free course; Labelling data with Snorkel; Bayesian Statistics.
Apache Spark, Bayesian, Data Preprocessing, Linear Algebra, Python
Essential Resources to Learn Bayesian Statistics - Jul 28, 2020.
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.
Bayesian, Machine Learning, Markov Chain, Statistics
- Practical Markov Chain Monte Carlo - Jun 26, 2020.
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.
Bayesian, Markov Chains, Monte Carlo, R
4 Free Math Courses to do and Level up your Data Science Skills - Jun 22, 2020.
Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.
Bayesian, Coursera, edX, Inference, Linear Algebra, Mathematics, Online Education, Principal component analysis, Probability, Python, Statistics
If you had to start statistics all over again, where would you start? - Jun 5, 2020.
If you are just diving into learning statistics, then where do you begin? Find insight from those who have tread in these waters before, and see what they might have done differently along their personal journeys in statistics.
Advanced Statistics, Advice, Bayesian, Career Advice, Statistician, Statistics
Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning - Jul 19, 2019.
This blog post is an overview of quantum machine learning written by the author of the paper Bayesian deep learning on a quantum computer. In it, we explore the application of machine learning in the quantum computing space. The authors of this paper hope that the results of the experiment help influence the future development of quantum machine learning.
Bayesian, Machine Learning, Quantum Computing
- XGBoost and Random Forest® with Bayesian Optimisation - Jul 8, 2019.
This article will explain how to use XGBoost and Random Forest with Bayesian Optimisation, and will discuss the main pros and cons of these methods.
Bayesian, Optimization, Python, random forests algorithm, XGBoost
- How to Automate Hyperparameter Optimization - Jun 12, 2019.
A step-by-step guide into performing a hyperparameter optimization task on a deep learning model by employing Bayesian Optimization that uses the Gaussian Process. We used the gp_minimize package provided by the Scikit-Optimize (skopt) library to perform this task.
Bayesian, Deep Learning, Hyperparameter, Machine Learning, Neural Networks, Optimization, Python, TensorFlow
- Towards Automatic Text Summarization: Extractive Methods - Mar 13, 2019.
The basic idea looks simple: find the gist, cut off all opinions and detail, and write a couple of perfect sentences, the task inevitably ended up in toil and turmoil. Here is a short overview of traditional approaches that have beaten a path to advanced deep learning techniques.
Bayesian, Deep Learning, Machine Learning, Sciforce, Text Analysis, Text Mining, Topic Modeling
- The Intuitions Behind Bayesian Optimization with Gaussian Processes - Oct 19, 2018.
Bayesian Optimization adds a Bayesian methodology to the iterative optimizer paradigm by incorporating a prior model on the space of possible target functions. This article introduces the basic concepts and intuitions behind Bayesian Optimization with Gaussian Processes.
Bayesian, Distribution, Hyperparameter, Machine Learning, Optimization
- Unfolding Naive Bayes From Scratch - Sep 25, 2018.
Whether you are a beginner in Machine Learning or you have been trying hard to understand the Super Natural Machine Learning Algorithms and you still feel that the dots do not connect somehow, this post is definitely for you!
Pages: 1 2
Bayesian, Classification, Naive Bayes, Probability, Statistics
5 Machine Learning Projects You Should Not Overlook - Feb 8, 2018.
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!
Bayesian, Gradient Boosting, Keras, Machine Learning, Overlook, PHP, Python, scikit-learn
What is a Bayesian Neural Network? - Dec 5, 2017.
BNNs are important in specific settings, especially when we care about uncertainty very much.
Bayesian, Bayesian Networks, Neural Networks
- How Bayesian Networks Are Superior in Understanding Effects of Variables - Nov 9, 2017.
Bayes Nets have remarkable properties that make them better than many traditional methods in determining variables’ effects. This article explains the principle advantages.
Bayesian, Bayesian Networks, Predictive Models, Probability, Regression, Statistics
- Vital Statistics You Never Learned… Because They’re Never Taught - Aug 29, 2017.
Marketing scientist Kevin Gray asks Professor Frank Harrell about some important things we often get wrong about statistics.
Bayesian, Data Science, Machine Learning, Statistics
- The Truth About Bayesian Priors and Overfitting - Jul 25, 2017.
Many of the considerations we will run through will be directly applicable to your everyday life of applying Bayesian methods to your specific domain.
Bayesian, Overfitting
- Introduction to Bayesian Inference - Dec 16, 2016.
Bayesian inference is a powerful toolbox for modeling uncertainty, combining researcher understanding of a problem with data, and providing a quantitative measure of how plausible various facts are. This overview from Datascience.com introduces Bayesian probability and inference in an intuitive way, and provides examples in Python to help get you started.
Bayesian, Datascience.com, Inference, Probability
How Bayesian Inference Works - Nov 15, 2016.
Bayesian inference isn’t magic or mystical; the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer. Read an in-depth overview here.
Pages: 1 2 3
Bayes Rule, Bayes Theorem, Bayesian, Inference, Statistics
5 EBooks to Read Before Getting into A Machine Learning Career - Oct 21, 2016.
A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.
Bayesian, Data Science, Deep Learning, Free ebook, Machine Learning, Reinforcement Learning
- Learning from Imbalanced Classes - Aug 31, 2016.
Imbalanced classes can cause trouble for classification. Not all hope is lost, however. Check out this article for methods in which to deal with such a situation.
Pages: 1 2
Balancing Classes, Bayesian, Learning from Data, Sampling, Tom Fawcett
- What Statistics Topics are Needed for Excelling at Data Science? - Aug 2, 2016.
Here is a list of skills and statistical concepts suggested for excelling at data science, roughly in order of increasing complexity.
Bayesian, Distribution, Machine Learning, Markov Chains, Probability, Regression, Statistics
- The Core of Data Science - Aug 1, 2016.
This post provides a simplifying framework, an ontology for Machine Learning and some important developments in dynamical machine learning. From first hand Data Science product experience, the author suggests how best to execute Data Science projects.
Bayesian, Data Science, Data Science Team, Ontology
Bayesian Machine Learning, Explained - Jul 13, 2016.
Want to know about Bayesian machine learning? Sure you do! Get a great introductory explanation here, as well as suggestions where to go for further study.
Bayesian, Explained, LDA, Machine Learning
- Top 10 Data Mining Algorithms, Explained - May 21, 2015.
Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.
Pages: 1 2 3
Algorithms, Apriori, Bayesian, Boosting, C4.5, CART, Data Mining, Explained, K-means, K-nearest neighbors, Naive Bayes, Page Rank, Support Vector Machines, Top 10
- Machine Learning in 7 Pictures - Mar 18, 2014.
Basic machine learning concepts of Bias vs Variance Tradeoff, Avoiding overfitting, Bayesian inference and Occam razor, Feature combination, Non-linear basis functions, and more - explained via pictures.
Basis functions, Bayesian, Concepts, Machine Learning, Pictures, Variance
