Machine Learning Algorithms

A comprehensive understanding of various machine learning algorithms—supervised, unsupervised, and reinforcement learning—is crucial. Knowing when and how to apply algorithms like decision trees, SVMs, k-nearest neighbors, and clustering is key to solving diverse problems.

A comprehensive understanding of various machine learning algorithms—supervised, unsupervised, and reinforcement learning—is crucial. Knowing when and how to apply algorithms like decision trees, SVMs, k-nearest neighbors, and clustering is key to solving diverse problems.

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Rutika Bhoir
Grad Student at Umass Amherst

There are some absolute legends out there teaching machine learning—and I hope I get to meet them in real life someday. Shout out to Dr. Charles Severance (Dr. Chuck!), who taught me Python when I was 19. I’ll never forget those lessons. Shout out to Kylie Ying, my comfort YouTuber and a total sweetheart—if you’re starting out, go subscribe. And of course, the OG himself: Andrew Ng. Please, please take his Machine Learning course on Coursera. The man is basically a machine learning fairy. He makes it all feel possible. The key with ML algorithms—whether it’s decision trees, SVMs, KNN, clustering, or reinforcement learning—isn’t memorizing everything. It’s understanding when and why to use them. It’s okay to not get it all at once. But with the right teacher? It clicks. There are so many accessible courses out there. And if money’s a barrier? Apply for financial aid on Coursera. I’ve done it. You just have to write a short essay and boom—free courses. Please don’t let cost stop you. You deserve to learn. So yeah—take the courses. Ask dumb questions. Break the code. Cry a little (it’s part of it). And keep going. You got this, sister.

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Rutika Bhoir
Grad Student at Umass Amherst

There are some absolute legends out there teaching machine learning—and I hope I get to meet them in real life someday. Shout out to Dr. Charles Severance (Dr. Chuck!), who taught me Python when I was 19. I’ll never forget those lessons. Shout out to Kylie Ying, my comfort YouTuber and a total sweetheart—if you’re starting out, go subscribe. And of course, the OG himself: Andrew Ng. Please, please take his Machine Learning course on Coursera. The man is basically a machine learning fairy. He makes it all feel possible. The key with ML algorithms—whether it’s decision trees, SVMs, KNN, clustering, or reinforcement learning—isn’t memorizing everything. It’s understanding when and why to use them. It’s okay to not get it all at once. But with the right teacher? It clicks. There are so many accessible courses out there. And if money’s a barrier? Apply for financial aid on Coursera. I’ve done it. You just have to write a short essay and boom—free courses. Please don’t let cost stop you. You deserve to learn. So yeah—take the courses. Ask dumb questions. Break the code. Cry a little (it’s part of it). And keep going. You got this, sister.

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