Machine Learning Nerds

[Introduction]
#10 Recap (Part 1): Basic

Welcome back to [Introduction] series episode 10. In the last episodes, we have discussed about how ML algorithms are categorized and challenges when processing data as well as creating models. This is the recap of what we have learn so that you can keep up with what happened.

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series 😀

[Do you know]
#5 History of Python
Welcome back to [Do you know] series. In this episode, we'll discuss about one of the most popular programming language - Python. We are also going to have a small python introduction course in reels soon

Hope you enjoy the video and don't miss our upcoming posts of [Do you know] series 😃

[Introduction]
#9 Main Challenges (Part 4): Underfitting

Welcome back to [Introduction] series episode 9. In the last episode, we mentioned about overfitting, a challenge in creating a model. In this episode, we'll intoduce another challenge when choosing algorithm

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series 😀

[A deeper insight]
#2 Stochastic Gradient Descent - SGD
Hi programmers, welcome the the next episode of [A deeper insight] series. In this episode, we'll continue introduce u to a classification algorithm

Hope you enjoy it and don't miss our upcoming posts of [A deeper insight] series 😀

[Introduction]
#8 Main Challenges (Part 3): Overfitting

Welcome back to [Introduction] series episode 8. In the last 2 episode, I talked about some challenges in training data. In this episode, we gonna talk about some difficulties in making a model.

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series 😀

[Introduction]
#7 Main Challenges (Part 2): Low-quality and irrelevent Training Data

Welcome back to [Introduction] series episode 7. In this episode, we gonna continue discuss about another challenges about training data.

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series 😀

[Introduction]
#6 Main Challenges (Part 1): Insufficient Quantity and Nonpresentative Training Data

Welcome back to [Introduction] series episode 6. This is a brand new topic about some challenges when training model. 😀

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series

[Do you know]
#3 Application of ML in the Economy
Welcome back to [Do you know] series. This week's topic will be about how Machine Learning has affected the Ecomony

Hope you enjoy the video and don't miss our upcoming posts of [Do you know] series 😃

[Introduction]
#5 Categorizing (Part 4): Instance-based & Model-based Learning

Welcome back to [Introduction] series episode 5. This episode, we gonna talk about 2 other types of algorithms in Machine Learning which is categorized based on how they generalize data

Hope you enjoy this episode and don't miss our upcoming posts of [Introduction] series 😃

[A deeper insight]
#1 KNN - K-Nearest Neighbors
Hi programmers, Machine Learning Nerds is now releasing a new series called [A deeper insight] that will explain some algorithms in Machine Learning.

The first episode will give some ideas about KNN, a supervised algorithm.

Hope you enjoy it and don't miss our upcoming posts of [A deeper insight] series 😀