Topic: Machine Learning
This page features most recent and most popular posts on Machine Learning.
Latest posts on Machine Learning
- Some Things Uber Learned from Running Machine Learning at Scale - Jul 7, 2020Uber machine learning runtime Michelangelo has been in operation for a few years. What has the Uber team learned?
- 5th International Summer School 2020 on Resource-aware Machine Learning (REAML) - Jul 7, 2020The Resource-aware Machine Learning summer school provides lectures on the latest research in machine learning, with the twist on resource consumption and how these can be reduced. This year it will be held online between 31st of August and 4th of September, and is free of charge. Register now.
Deploy Machine Learning Pipeline on AWS Fargate - Jul 3, 2020A step-by-step beginner’s guide to containerize and deploy ML pipeline serverless on AWS Fargate.- KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills - Jun 24, 2020A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset
- Machine Learning in Dask - Jun 22, 2020In this piece, we’ll see how we can use Dask to work with large datasets on our local machines.
Most popular (badge-winning) recent posts on Machine Learning
- Deploy Machine Learning Pipeline on AWS Fargate [Gold Blog]A step-by-step beginner’s guide to containerize and deploy ML pipeline serverless on AWS Fargate.
- Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning [Silver Blog]The new framework allow developers with minimum experience to create and train machine learning models.
- Naïve Bayes Algorithm: Everything you need to know [Silver Blog]Naïve Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks. In this article, we will understand the Naïve Bayes algorithm and all essential concepts so that there is no room for doubts in understanding.
- Model Evaluation Metrics in Machine Learning [Silver Blog]A detailed explanation of model evaluation metrics to evaluate a classification machine learning model.
- Build and deploy your first machine learning web app [Gold Blog]A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.
- An easy guide to choose the right Machine Learning algorithm [Silver Blog]There's no free lunch in machine learning. So, determining which algorithm to use depends on many factors from the type of problem at hand to the type of output you are looking for. This guide offers several considerations to review when exploring the right ML approach for your dataset.
- Automated Machine Learning: The Free eBook [Gold Blog]There is a lot to learn about automated machine learning theory and practice. This free eBook can get you started the right way.
- AI and Machine Learning for Healthcare [Gold Blog]Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.
- Start Your Machine Learning Career in Quarantine [Gold Blog]While this quarantine can last two months, make the most of it by starting your career in Machine Learning with this 60-day learning plan.
- Beginners Learning Path for Machine Learning [Gold Blog]So, you are interested in machine learning? Here is your complete learning path to start your career in the field.
- Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition [Gold Blog]If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.
- Can Java Be Used for Machine Learning and Data Science? [Gold Blog]While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.
- 10 Must-read Machine Learning Articles (March 2020) [Gold Blog]This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.
- How to Do Hyperparameter Tuning on Any Python Script in 3 Easy Steps [Silver Blog]With your machine learning model in Python just working, it's time to optimize it for performance. Follow this guide to setup automated tuning using any optimization library in three steps.
- Mathematics for Machine Learning: The Free eBook [Platinum Blog]Check out this free ebook covering the fundamentals of mathematics for machine learning, as well as its companion website of exercises and Jupyter notebooks.
- Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs [Platinum Blog]From network security to financial fraud, anomaly detection helps protect businesses, individuals, and online communities. To help improve anomaly detection, researchers have developed a new approach called MIDAS.
- How (not) to use Machine Learning for time series forecasting: The sequel [Gold Blog]Developing machine learning predictive models from time series data is an important skill in Data Science. While the time element in the data provides valuable information for your model, it can also lead you down a path that could fool you into something that isn't real. Follow this example to learn how to spot trouble in time series data before it's too late.
- 24 Best (and Free) Books To Understand Machine Learning [Platinum Blog]We have compiled a list of some of the best (and free) machine learning books that will prove helpful for everyone aspiring to build a career in the field.
- A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM) [Silver Blog]Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.
- Resources for Women in AI, Data Science, and Machine Learning [Silver Blog]For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) [Platinum Blog]We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.
