Top 10 posts to Master Basic Machine Learning on DEV
Tags: machinelearning, bestofdev, beginners
Published: 2020-06-27 19:11:06

> ## " A breakthrough in Machine Learning would be worth ten Microsofts" -**Bill Gates**


The above quote from Bill Gates emphasizes the importance of Machine Learning and why should we know about it. It is technology one must be aware of and at least know the basics. In the near future, most of our devices are going to be affected by this technology.

As we know that first a baby learns to crawl, then it gradually walks and after a fair amount of time it starts to run. This process is also reflected in the learning of any new technology. 

So here I am presenting 10 best posts from DEV which will help you take the baby steps in learning *Machine Learning*. Slowly and gradually we will be at a stage where we will be building huge Machine Learning models and deploying it in the real world.

# Introduction and Summary


This post beautifully explains the Machine Learning terms and summarizes them with the help of infographics. It has covered almost all the definitions of Machine Learning.


{% link https://dev.to/sri07spec/a-layman-s-guide-to-machine-learning-ai-and-deep-learning-62f %}


# Meeting the ML algorithms


This post has introduced us to the 5 most popular Machine Learning algorithms namely **Linear regression**, **Logistic regression**, **Naive Bayes**, **KNN**, and **Random forest**.


{% link https://dev.to/twilio/top-5-machine-learning-algorithms-you-need-to-know-2723 %}


# First ML algorithm you learn


**Linear regression** is the first algorithm that most of us learn during our course of learning ML. In this post the author has very elegantly and concisely explained this algorithm.


{% link https://dev.to/nexttech/introduction-to-linear-regression-in-python-2g5b %}


# The more you learn the better you are


This post is another gem from the vast sea of blogs of DEV. It has gracefully described another ML algorithm **K-Means Clustering**. It is one of the most popular unsupervised Machine Learning algorithms. 


{% link https://dev.to/taillogs/ml-engineering-series-1-intro-to-k-means-clustering-4cjh %}


# Tools are a must


How has the discovery of wheel affected the human evolution? Answering this question helps us identify the importance of tools in our life. **scikit-learn** is a must-know tool for ML beginners. This is a basic guide to the scikit-learn python library.


{% link https://dev.to/duomly/what-is-scikit-learn-a-beginner-guide-to-popular-machine-learning-python-library-1f06 %}


# What goes behind Machine Learning


Machine learning is basically Mathematics and Statistics in disguise. We must know mathematics to better understand the concepts of ML. 


{% link https://dev.to/rohitpatil5/basic-mathematics-for-machine-learning-d2a %}


# A complete meal


The above mentioned posts are just small size appetizers. Here I present to you the complete meal. This 7 part series will help you master the basics in one go. It has all the components mixed well enough to fulfill your hunger for knowledge on ML.


{% link https://dev.to/apoorvadave/beginning-with-machine-learning---part-1-pbl %}


## The other BIG guy


Neural networks is another entity that must be mastered to become an ML expert. This two-part series alluringly explains Artificial Neural Networks and then gradually progresses to Convolutional Neural Networks, which is the most heavily used image classification algorithm. It's a must-read post and need of the hour.


{% link https://dev.to/nestedsoftware/neural-networks-primer-374i %}


# Talk of the town


Here the author has nicely described the deep learning algorithms and its uses. Deep learning is the talk of the town in ML community. It is the newest but mostly used member of ML models. 


{% link https://dev.to/nexttech/deep-learning-basics-a-crash-course-1hc2 %}


# Lets apply our LEARNING


After a lot of theoretical and basic content, it's now our turn to make our hands dirty by engaging in some practicality. This post has a collection of ML models for beautiful small projects which you can try to build yourself. 


{% link https://dev.to/trekhleb/interactive-machine-learning-experiments-3ga7 %}


I have tried my level best to bring cherry-picked content for the people of #DEVCommunity who are interested in Machine Learning. Happy Learning and please don't forget to upvote and bookmark this post if you liked it.

Also, I would request the people to follow the tag {% tag machinelearning %} as more and more awesome content is going to come. Please, help us build a stronger Machine Learning community here on DEV. If anyone wants to see Machine Learning posts to appear more frequently in their feed adjust the TAG WEIGHT to 10 in your followed tags section on Dashboard.