6 Predictive Models Every Beginner Data Scientist Should Master - Dec 23, 2021.
Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.
Linear Regression, Logistic Regression, Machine Learning, random forests algorithm
- A Comprehensive Guide to Ensemble Learning – Exactly What You Need to Know - May 6, 2021.
This article covers ensemble learning methods, and exactly what you need to know in order to understand and implement them.
CatBoost, Ensemble Methods, Machine Learning, Python, random forests algorithm, scikit-learn, XGBoost
- 3 Reasons to Use Random Forest® Over a Neural Network: Comparing Machine Learning versus Deep Learning - Apr 8, 2020.
Both the random forest algorithm and Neural Networks are different techniques that learn differently but can be used in similar domains. Why would you use one over the other?
Machine Learning, Neural Networks, random forests algorithm
- Random Forest® — A Powerful Ensemble Learning Algorithm - Jan 22, 2020.
The article explains the Random Forest algorithm and how to build and optimize a Random Forest classifier.
Algorithms, Ensemble Methods, Python, random forests algorithm
- Random Forest® vs Neural Networks for Predicting Customer Churn - Dec 26, 2019.
Let us see how random forest competes with neural networks for solving a real world business problem.
Churn, Customer Analytics, Neural Networks, random forests algorithm
- Comparing Decision Tree Algorithms: Random Forest® vs. XGBoost - Aug 21, 2019.
Check out this tutorial walking you through a comparison of XGBoost and Random Forest. You'll learn how to create a decision tree, how to do tree bagging, and how to do tree boosting.
ActiveState, Decision Trees, Python, random forests algorithm, XGBoost
- Coding Random Forests® in 100 lines of code* - Aug 7, 2019.
There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks.
Algorithms, Machine Learning, Multicollinearity, R, random forests algorithm
- 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
- KDnuggets™ News 19:n22, Jun 12: The Modern Open-Source Data Science/Machine Learning Ecosystem; Simplifying the Data Visualisation Process in Python - Jun 12, 2019.
The 6 tools in the modern open-source Data Science ecosystem; Simplifying the Data Visualisation Process in Python; The Infinity Stones of Data Science; Best resources for developers transitioning into data science.
Data Science Platform, Data Visualization, Machine Learning, Neural Networks, random forests algorithm
Random Forests® vs Neural Networks: Which is Better, and When? - Jun 7, 2019.
Random Forests and Neural Network are the two widely used machine learning algorithms. What is the difference between the two approaches? When should one use Neural Network or Random Forest?
Decision Trees, Neural Networks, random forests algorithm
- KDnuggets™ News 19:n13, Apr 3: Top 10 Data Scientist Coding Mistakes; Explaining Random Forest®; Which Face is Real? - Apr 3, 2019.
Do you know when is using "for" loop a mistake? Read 10 top coding mistakes by Data Scientists; Understand Random Forests and Linear Regression with scikit-learn; Find how to choose the right chart type; and see if you can guess which face is real.
Data Visualization, Linear Regression, Mistakes, random forests algorithm
Explaining Random Forest® (with Python Implementation) - Mar 29, 2019.
We provide an in-depth introduction to Random Forest, with an explanation to how it works, its advantages and disadvantages, important hyperparameters and a full example Python implementation.
Explained, Machine Learning, Python, random forests algorithm
- KDnuggets™ News 19:n06, Feb 6: Data Scientists: Why are they so expensive to hire? An Essential Data Science Venn Diagram - Feb 6, 2019.
Also an overview of main methods for Dimension Reduction; an intuitive explanation of Random Forests®; how to avoid data visualization disasters; and trending Deep Learning Github repos.
Data Scientist, Dimensionality Reduction, Hiring, random forests algorithm, Venn Diagram
- Random forests® explained intuitively - Jan 30, 2019.
A detailed explanation of random forests, with real life use cases, a discussion into when a random forest is a poor choice relative to other algorithms, and looking at some of the advantages of using random forest.
Decision Trees, Explained, random forests algorithm
Data Scientist Interviews Demystified - Aug 2, 2018.
We look at typical questions in a data science interview, examine the rationale for such questions, and hope to demystify the interview process for recent graduates and aspiring data scientists.
Data Science Skills, Hiring, Interview Questions, P-value, random forests algorithm, XGBoost
- Introduction to Python Ensembles - Feb 9, 2018.
In this post, we'll take you through the basics of ensembles — what they are and why they work so well — and provide a hands-on tutorial for building basic ensembles.
Pages: 1 2
Decision Trees, Ensemble Methods, Machine Learning, Python, random forests algorithm, ROC-AUC, scikit-learn, XGBoost
Top Data Science and Machine Learning Methods Used in 2017 - Dec 11, 2017.
The most used methods are Regression, Clustering, Visualization, Decision Trees/Rules, and Random Forests; Deep Learning is used by only 20% of respondents; we also analyze which methods are most "industrial" and most "academic".
Pages: 1 2
Algorithms, Clustering, Data Science, Deep Learning, Machine Learning, Poll, random forests algorithm, Regression, Uplift Modeling
- KDnuggets™ News 17:n40, Oct 18: Want to Become a Data Scientist? Read This!; Natural Stupidity is more Dangerous than Artificial Intelligence - Oct 18, 2017.
Want to Become a Data Scientist? Read This Interview First; Natural Stupidity is more Dangerous than Artificial Intelligence; Random Forests(r), Explained; Key Trends and Takeaways from RE-WORK Deep Learning Summit Montreal; An Overview of 3 Popular Courses on Deep Learning
AI, Bias, Data Science, Data Science Platform, Data Scientist, Deep Learning, MOOC, random forests algorithm, RE.WORK
Random Forests®, Explained - Oct 17, 2017.
Random Forest, one of the most popular and powerful ensemble method used today in Machine Learning. This post is an introduction to such algorithm and provides a brief overview of its inner workings.
Algorithms, CART, Decision Trees, Ensemble Methods, Explained, Machine Learning, random forests algorithm, Salford Systems
Understanding Machine Learning Algorithms - Oct 3, 2017.
Machine learning algorithms aren’t difficult to grasp if you understand the basic concepts. Here, a SAS data scientist describes the foundations for some of today’s popular algorithms.
Algorithms, Ensemble Methods, Gradient Boosting, Machine Learning, Neural Networks, Predictive Analytics, random forests algorithm, SVM
- Learn How to Make Machine Learning Work (webinars every Tue in October, Live or on-demand) - Sep 28, 2017.
To fully use machine learning, we first need to understand both the potential benefits and the techniques to create data-driven models. In this webinar series, we will show you how to easily and automatically apply complex algorithms to data in real world applications.
CART, Machine Learning, Minitab, random forests algorithm, Regression, Salford Systems
- Webinar: Improve Your CLASSIFICATION with CART(r) and RandomForests(r), Mar 29 - Mar 27, 2017.
We discuss the advantages of tree based techniques, including automatic variable selection, variable interactions, nonlinear relationships, outliers, and missing values.
CART, Classification, random forests algorithm, Salford Systems
Getting Up Close and Personal with Algorithms - Mar 21, 2017.
We've put together a brief summary of the top algorithms used in predictive analysis, which you can see just below. Read to learn more about Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, and more.
Algorithms, Dataiku, Decision Trees, Gradient Boosting, Linear Regression, Logistic Regression, random forests algorithm
- KDnuggets™ News 16:n43, Dec 7: Where did you use Data Science? The hard thing about Deep Learning; Big Data Main Events in 2016, Key Trends for 2017 - Dec 7, 2016.
Where did you apply Analytics, Data Science in 2016? Big Data Main Developments in 2016 and Key Trends in 2017; The Data Science Delusion; The hard thing about deep learning.
2017 Predictions, Data Science, Deep Learning, random forests algorithm
- Random Forests® in Python - Dec 2, 2016.
Random forest is a highly versatile machine learning method with numerous applications ranging from marketing to healthcare and insurance. This is a post about random forests using Python.
Algorithms, Classification, Ensemble Methods, Python, random forests algorithm, Yhat
- The Evolution of Classification, Oct 19, Oct 26 Webinars - Oct 7, 2016.
Join us for this two part webinar series on the Evolution of Classification, presented by Senior Scientist, Mikhail Golovnya.
Classification, Logistic Regression, random forests algorithm, Salford Systems, SVM
- The Great Algorithm Tutorial Roundup - Sep 20, 2016.
This is a collection of tutorials relating to the results of the recent KDnuggets algorithms poll. If you are interested in learning or brushing up on the most used algorithms, as per our readers, look here for suggestions on doing so!
Algorithms, Clustering, Decision Trees, K-nearest neighbors, Machine Learning, PCA, Poll, random forests algorithm, Regression, Statistics, Text Mining, Time Series, Visualization
- Random Forest®: A Criminal Tutorial - Sep 19, 2016.
Get an overview of Random Forest here, one of the most used algorithms by KDnuggets readers according to a recent poll.
Algobeans, CA, Crime, random forests algorithm, San Francisco
- Webinar: Modern Regression Modeling for Voter MicroTargeting, Sep 14, Sep 21 - Sep 7, 2016.
Join us for a special 2-part webinar about voting trends, and we will show how machine learning models and data science can be used in elections.
Elections, Gradient Boosting, Linear Regression, random forests algorithm, Salford Systems
- Improve Your Regression with Modern Regression Analysis Techniques, July 27, Aug 10 Webinars - Jul 22, 2016.
This two part webinar will help you improve your regression using modern regression analysis techniques. July 27 (part 1) and August 10 (part 2).
random forests algorithm, Regression, Salford Systems
- KDnuggets™ News 16:n15, Apr 27: Deep Learning vs. SVMs, Random Forests; Python Guide for Data Science - Apr 27, 2016.
When Does Deep Learning Work Better Than SVMs or Random Forests; Comprehensive Guide to Learning Python for Data Science; Top 10 IPython Notebook Tutorials for Data Science and Machine Learning; 5,000 KDnuggets Posts - Examining Our Most Popular Content
Deep Learning, IPython, Python, random forests algorithm, Support Vector Machines
When Does Deep Learning Work Better Than SVMs or Random Forests®? - Apr 22, 2016.
Some advice on when a deep neural network may or may not outperform Support Vector Machines or Random Forests.
Advice, Deep Learning, random forests algorithm, Support Vector Machines, SVM
- Jan 27 Webinar: 3 Ways to Improve your Regression, Part 2 - Jan 26, 2016.
How to take data science techniques even further to extract actionable insight and take advantage of advanced modeling features. You will walk away with several different methods to turn your ordinary regression into an extraordinary regression!
Gradient Boosting, MARS, random forests algorithm, Regression, Salford Systems
- 3 Ways to Improve your Regression, Jan 20 & 27 Webinars, Hands-on - Jan 12, 2016.
Instead of proceeding with a mediocre analysis, join us for this 2-part webinar series. We will show you how modern algorithms can take your regression model to the next level and expertly handle your modeling woes
Gradient Boosting, MARS, random forests algorithm, Regression, Salford Systems
- Topological Analysis and Machine Learning: Friends or Enemies? - Sep 29, 2015.
What is the interaction between Topological Data Analysis and Machine Learning ? A case study shows how TDA decomposition of the data space provides useful features for improving Machine Learning results.
Ayasdi, Machine Learning, random forests algorithm, Topological Data Analysis
- Top 10 Quora Machine Learning Writers and Their Best Advice - Sep 18, 2015.
Top Quora machine learning writers give their advice on pursuing a career in the field, academic research, and selecting and using appropriate technologies.
Machine Learning, Quora, random forests algorithm, Top 10, Xavier Amatriain, Yoshua Bengio
- Top KDnuggets tweets, Aug 25-31: How to become a #DataScientist for Free; The R universe of Hadley Wickham - Sep 1, 2015.
How to become a Data Scientist for Free; #BigData is Out, #MachineLearning is in; The universe of Hadley Wickham, the Man Who Revolutionized R; Book review: Fundamentals of #DeepLearning.
Big Data Architecture, Data Science Education, Deep Learning, Hadley Wickham, Nikhil Buduma, R, random forests algorithm
- Top 10 R Packages to be a Kaggle Champion - Apr 21, 2015.
Kaggle top ranker Xavier Conort shares insights on the “10 R Packages to Win Kaggle Competitions”.
Kaggle, R Packages, random forests algorithm, Success, SVM, Text Analysis, Xavier Conort
- Machine Learning 201: Does Balancing Classes Improve Classifier Performance? - Apr 9, 2015.
The author investigates if balancing classes improves performance for logistic regression, SVM, and Random Forests, and finds where it helps the performance and where it does not.
Pages: 1 2 3
Balancing Classes, random forests algorithm, Regression, SVM
- Top KDnuggets tweets, Dec 7-14: Google new CAPTCHA trains #AI; Random Forests, SVM give best results - Dec 15, 2014.
Which one is the bunny? Google new CAPTCHA bot-trap trains #AI; O'Reilly Data Scientist Salary and Tools Survey 2014; Microsoft brings the power of #MachineLearning to Office Online; 10 Data Science Newsletters to Subscribe to.
CAPTCHA, Data Science Skills, Google, Machine Learning, Microsoft, random forests algorithm, Salary, SVM
- Comprehensive Data Science Training by Salford Systems, Dec 3-5, Online or San Diego - Nov 4, 2014.
Learn the basics tree-structured data mining with CART, and progress to more advanced topics including Linear, Logistic, Nonlinear, Regularized, Lasso, MARS, TreeNet (Stochastic Gradient Boosting) and RandomForests(r), including Latest Refinements and Model Compression.
CART, Data Mining Training, MARS, Online Education, random forests algorithm, Salford Systems, San Diego-CA
- Salford Comprehensive Data Science Training, Dec 3-5, San Diego or Online - Oct 21, 2014.
Learn the basics tree-structured data mining with CART, and progress to more advanced topics including Linear, Logistic, Nonlinear, Regularized, Lasso, MARS, TreeNet (Stochastic Gradient Boosting) and RandomForests(r), including Latest Refinements and Model Compression.
CART, Data Mining Training, MARS, Online Education, random forests algorithm, Salford Systems, San Diego-CA
- Top KDnuggets tweets, Jul 18-20: Baby steps in Learning Python; 7 Steps for Learning Data Mining - Jul 21, 2014.
Baby steps in learning #Python for data analysis; My 7 Steps for Learning Data Mining and Data Science - now in Techopedia; A good collection of #MachineLearning tools in #Python; Understanding Random Forests: From Theory to Practice - implementation.
Data Science Education, Python, random forests algorithm, Techopedia, World Cup
- Top stories for Mar 2-8: Do’s and Don’t of Data Mining; Wolfram Breakthtough language - Mar 9, 2014.
The Dos and Donts of Data Mining; Wolfram Breakthrough Knowledge-based Programming Language - what it means for Data Science? Introduction to Random Forests for Beginners - free ebook; Exclusive Interview with Quentin Clark, Microsoft Data Platform Group.
Data Mining, ebook, Interview, Microsoft, Quentin Clark, random forests algorithm, Wolfram
- Top KDnuggets tweets, Mar 5-6: Data Science Backlash begins; Intro to Random Forests® for Beginners – free ebook - Mar 7, 2014.
Backlash begins: Data Science is not a science, and not a good job prospect; Intro to Random Forests for Beginners - free ebook; Must read for data scientists: Q - new Data Language; Book: R for Business Analytics.
Backlash, Data Definition, Data Science, ebook, Q, R, random forests algorithm
- Introduction to Random Forests® for Beginners – free ebook - Mar 6, 2014.
Random Forests is of the most powerful and successful machine learning techniques. This free ebook will help beginners to leverage the power of Random Forests.
Beginners, Decision Trees, ebook, Free, Kaggle, random forests algorithm, Salford Systems
