Machine learning, deep learning, and AI are enabling transformational change in all fields from medicine to music. It is helping…
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Nested Cross-Validation for Machine Learning with Python
The k-fold cross-validation procedure is used to estimate the performance of machine learning models when making predictions on data not…
Continue ReadingLOOCV for Evaluating Machine Learning Algorithms
The Leave-One-Out Cross-Validation, or LOOCV, procedure is used to estimate the performance of machine learning algorithms when they are used…
Continue Reading10 Techniques to deal with Imbalanced Classes in Machine Learning
OverviewGet familiar with class imbalanceUnderstand various techniques to treat imbalanced classes such as-Random under-samplingRandom over-samplingNearMissYou can check the implementation of…
Continue ReadingTrain-Test Split for Evaluating Machine Learning Algorithms
The train-test split procedure is used to estimate the performance of machine learning algorithms when they are used to make…
Continue ReadingTop Five Data Privacy Issues that Artificial Intelligence and Machine Learning Startups Need to Know
In this special guest feature, Joseph E. Mutschelknaus, a director in Sterne Kessler’s Electronics Practice Group, addresses some of the…
Continue ReadingWhat I learned from looking at 200 machine learning tools
By Chip Huyen, a writer and computer scientist, currently at an ML startup in Silicon Valley. To better understand the…
Continue ReadingHow to Selectively Scale Numerical Input Variables for Machine Learning
Many machine learning models perform better when input variables are carefully transformed or scaled prior to modeling. It is convenient,…
Continue ReadingAdd Binary Flags for Missing Values for Machine Learning
Missing values can cause problems when modeling classification and regression prediction problems with machine learning algorithms. A common approach is…
Continue ReadingBest of arXiv.org for AI, Machine Learning, and Deep Learning – June 2020
In this recurring monthly feature, we filter recent research papers appearing on the arXiv. org preprint server for compelling subjects…
Continue ReadingThe Bitter Lesson of Machine Learning
By Richard Sutton, DeepMind and U. of Alberta. The biggest lesson that can be read from 70 years of AI…
Continue ReadingFramework for Data Preparation Techniques in Machine Learning
There are a vast number of different types of data preparation techniques that could be used on a predictive modeling…
Continue ReadingSpecial Report: The State of AI and Machine Learning
Appen Limited, a leading provider of high-quality training data for organizations that build effective AI systems at scale, released its…
Continue ReadingHow to Use Feature Extraction on Tabular Data for Machine Learning
Machine learning predictive modeling performance is only as good as your data, and your data is only as good as…
Continue ReadingReal-World Machine Learning Case Study: Clustering Transactions Based on Text Descriptions
Introduction We are living in the era of digital technologies. When was the last time you walked into a shop…
Continue ReadingHow to Choose Data Preparation Methods for Machine Learning
Data preparation is an important part of a predictive modeling project. Correct application of data preparation will transform raw data…
Continue Reading4 Simple Ways to Split a Decision Tree in Machine Learning
Overview How do you split a decision tree? What are the different splitting criteria when working with decision trees? Learn…
Continue ReadingData Preparation for Machine Learning (7-Day Mini-Course)
Data preparation involves transforming raw data into a form that is more appropriate for modeling. Preparing data may be the…
Continue ReadingWhere Predictive Machine Learning Falls Short and What We Can Do About It
Even at this early stage of the game, machine learning holds much promise, and is being applied to incredibly diverse…
Continue Reading22 Widely Used Data Science and Machine Learning Tools in 2020
Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a…
Continue Reading3 Building Blocks of Machine Learning you Should Know as a Data Scientist
Overview A machine learning system consists of multiple building blocks that need to be managed Learn about the three key…
Continue ReadingMachine Learning Engineer vs Data Scientist (Is Data Science Over?)
By Jason Jung, Data Scientist at GoDaddy, blogger, and hacker. I work as a data scientist (which we will define…
Continue ReadingAccelerated Machine Learning Available from Your Browser
Data scientists and ML engineers can now speedup their applications using the power of FPGA accelerators from their browser. FPGAs…
Continue ReadingkNN Imputation for Missing Values in Machine Learning
Datasets may have missing values, and this can cause problems for many machine learning algorithms. As such, it is good…
Continue ReadingAUC-ROC Curve in Machine Learning Clearly Explained
AUC-ROC Curve – The Star Performer! You’ve built your machine learning model – so what’s next? You need to evaluate…
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