Topic: Machine Learning
This page features most recent and most popular posts on Machine Learning.
Latest posts on Machine Learning
- LinkedIn’s Pro-ML Architecture Summarizes Best Practices for Building Machine Learning at Scale - Sep 23, 2020The reference architecture is powering mission critical machine learning workflows within LinkedIn.
- How I Consistently Improve My Machine Learning Models From 80% to Over 90% Accuracy - Sep 23, 2020Data 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.
- KDnuggets™ News 20:n36, Sep 23: New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project - Sep 23, 2020New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python; Online Certificates/Courses in AI, Data Science, Machine Learning; Can Neural Networks Show Imagination?
- Machine Learning from Scratch: Free Online Textbook - Sep 22, 2020If 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.
- What an Argentine Writer and a Hungarian Mathematician Can Teach Us About Machine Learning Overfitting - Sep 21, 2020This article presents some beautiful ideas about intelligence and how they related to modern machine learning.
Most popular (badge-winning) recent posts on Machine Learning
- 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.
- 4 ways to improve your TensorFlow model – key regularization techniques you need to know [Gold Blog]Regularization techniques are crucial for preventing your models from overfitting and enables them perform better on your validation and test sets. This guide provides a thorough overview with code of four key approaches you can use for regularization in TensorFlow.
- Top Google AI, Machine Learning Tools for Everyone [Silver Blog]Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.
- Going Beyond Superficial: Data Science MOOCs with Substance [Silver Blog]Data science MOOCs are superficial. At least, a lot of them are. What are your options when looking for something more substantive?
- Setting Up Your Data Science & Machine Learning Capability in Python [Silver Blog]With the rich and dynamic ecosystem of Python continuing to be a leading programming language for data science and machine learning, establishing and maintaining a cost-effective development environment is crucial to your business impact. So, do you rent or buy? This overview considers the hidden and obvious factors involved in selecting and implementing your Python platform.
- Awesome Machine Learning and AI Courses [Gold Blog]Check out this list of awesome, free machine learning and artificial intelligence courses with video lectures.
- Essential Resources to Learn Bayesian Statistics [Silver Blog]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.
- Wrapping Machine Learning Techniques Within AI-JACK Library in R [Silver Blog]The article shows an approach to solving problem of selecting best technique in machine learning. This can be done in R using just one library called AI-JACK and the article shows how to use this tool.
- The Bitter Lesson of Machine Learning [Gold Blog]Since that renowned conference at Dartmouth College in 1956, AI research has experienced many crests and troughs of progress through the years. From the many lessons learned during this time, some have needed to be re-learned -- repeatedly -- and the most important of which has also been the most difficult to accept by many researchers.
- 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.
- Understanding Machine Learning: The Free eBook [Silver Blog]Time to get back to basics. This week we have a look at a book on foundational machine learning concepts, Understanding Machine Learning: From Theory to Algorithms.
- 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.
