RemoteCoded - Podcast 01: A Deep Dive Into Machine Learning Algorithms
Welcome to today’s episode of our podcast, where we explore the core algorithms that power machine learning and AI. This episode is designed to complement our Machine Learning Algorithms Cheat Sheet, which you can download as a PDF from the blog.
In this episode, we’ll break down the most commonly used machine learning algorithms, covering both supervised and unsupervised techniques, as well as reinforcement learning and deep learning models. You’ll get insights into how these algorithms are used in real-world applications, from predicting customer behavior to enabling self-driving cars.
Whether you’re looking for a quick refresher or are just starting out in AI, this podcast, along with the cheat sheet, will give you a clear understanding of:
Supervised Learning (e.g., Linear Regression, Random Forest)
Unsupervised Learning (e.g., k-Means Clustering, PCA)
Reinforcement Learning (e.g., Q-Learning, PPO)
Deep Learning (e.g., CNNs, RNNs)
Tune in to learn the key concepts behind each algorithm and how you can apply them using popular Python libraries like scikit-learn, TensorFlow, and PyTorch. Don't forget to download your Cheat Sheet PDF for easy reference, and follow along as we dive into the details in this episode!
