Topic: Machine Learning
This page features most recent and most popular posts on Machine Learning.
Latest posts on Machine Learning
- The Ultimate Scikit-Learn Machine Learning Cheatsheet - Jan 25, 2021With the power and popularity of the scikit-learn for machine learning in Python, this library is a foundation to any practitioner's toolset. Preview its core methods with this review of predictive modelling, clustering, dimensionality reduction, feature importance, and data transformation.
Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants - Jan 22, 2021
Kaggle’s survey of ‘State of Data Science and Machine Learning 2020’ covers a lot of diverse topics. In this post, we are going to look at the popularity of cloud computing platforms and products among the data science and ML professionals participated in the survey.- How to Use MLOps for an Effective AI Strategy - Jan 21, 2021The need to deal with the challenges and other smaller nuances of deploying machine learning models has given rise to the relatively new concept of MLOps. – a set of best practices aimed at automating the ML lifecycle, bringing together the ML system development and ML system operations.
- Going Beyond the Repo: GitHub for Career Growth in AI & Machine Learning - Jan 21, 2021Many online tools and platforms exist to help you establish a clear and persuasive online profile for potential employers to review. Have you considered how your go-to online code repository could also help you land your next job?
- Popular Machine Learning Interview Questions - Jan 20, 2021Get ready for your next job interview requiring domain knowledge in machine learning with answers to these eleven common questions.
Most popular (badge-winning) recent posts on Machine Learning
- Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants [Gold Blog]Kaggle’s survey of ‘State of Data Science and Machine Learning 2020’ covers a lot of diverse topics. In this post, we are going to look at the popularity of cloud computing platforms and products among the data science and ML professionals participated in the survey.
- K-Means 8x faster, 27x lower error than Scikit-learn in 25 lines [Gold Blog]K-means clustering is a powerful algorithm for similarity searches, and Facebook AI Research's faiss library is turning out to be a speed champion. With only a handful of lines of code shared in this demonstration, faiss outperforms the implementation in scikit-learn in speed and accuracy.
- All Machine Learning Algorithms You Should Know in 2021 [Gold Blog]Many machine learning algorithms exits that range from simple to complex in their approach, and together provide a powerful library of tools for analyzing and predicting patterns from data. If you are learning for the first time or reviewing techniques, then these intuitive explanations of the most popular machine learning models will help you kick off the new year with confidence.
- 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 [Platinum Blog]We present a curated list of 15 free eBooks compiled in a single location to close out the year.
- State of Data Science and Machine Learning 2020: 3 Key Findings [Gold Blog]Kaggle recently released its State of Data Science and Machine Learning report for 2020, based on compiled results of its annual survey. Read about 3 key findings in the report here.
- Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology [Gold Blog]Our panel of leading experts reviews 2020 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 [Silver Blog]2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.
- Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision [Gold Blog]This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.
- Top 5 Free Machine Learning and Deep Learning eBooks Everyone should read [Gold Blog]There is always so much new to learn in machine learning, and keeping well grounded in the fundamentals will help you stay up-to-date with the latest advancements while acing your career in Data Science.
- Top Python Libraries for Data Science, Data Visualization & Machine Learning [Platinum Blog]This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.
- An Introduction to AI, updated [Silver Blog]We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.
- How to Explain Key Machine Learning Algorithms at an Interview [Gold Blog]While preparing for interviews in Data Science, it is essential to clearly understand a range of machine learning models -- with a concise explanation for each at the ready. Here, we summarize various machine learning models by highlighting the main points to help you communicate complex models.
- Annotated Machine Learning Research Papers [Silver Blog]Check out this collection of annotated machine learning research papers, and no longer fear their reading.
- How LinkedIn Uses Machine Learning in its Recruiter Recommendation Systems [Silver Blog]LinkedIn uses some very innovative machine learning techniques to optimize candidate recommendations.
- Free Introductory Machine Learning Course From Amazon [Silver Blog]Amazon's Machine Learning University offers an introductory course titled Accelerated Machine Learning, which is a good starting place for those looking for a foundation in generalized practical ML.
- 10 Best Machine Learning Courses in 2020 [Gold Blog]If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.
- How I Consistently Improve My Machine Learning Models From 80% to Over 90% Accuracy [Silver Blog]Data science work typically requires a big lift near the end to increase the accuracy of any model developed. These five recommendations will help improve your machine learning models and help your projects reach their target goals.
- Machine Learning from Scratch: Free Online Textbook [Gold Blog]If you are looking for a machine learning starter that gets right to the core of the concepts and the implementation, then this new free textbook will help you dive in to ML engineering with ease. By focusing on the basics of the underlying algorithms, you will be quickly up and running with code you construct yourself.
- Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities [Silver Blog]We present the online courses and certificates in AI, Data Science, Machine Learning, and related topics from the top 20 universities in the world.
- 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out [Silver Blog]If you are just starting down a path toward a career in Data Science, or you are already a seasoned practitioner, then keeping active to advance your experience through side projects is invaluable to take you to the next professional level. These eight interesting project ideas with source code and reference articles will jump start you to thinking outside of the box.
- How to Evaluate the Performance of Your Machine Learning Model [Silver Blog]You can train your supervised machine learning models all day long, but unless you evaluate its performance, you can never know if your model is useful. This detailed discussion reviews the various performance metrics you must consider, and offers intuitive explanations for what they mean and how they work.