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Part 1 ~ Machine Learning Algorithms Will Finally Make Sense After This In this video, we break down machine learning in the simplest way possible, not as a complex theory, but as a set of practical tools used to solve real-world problems. Starting from Linear Regression, we move through Logistic Regression, Decision Trees, Support Vector Machines, K-Nearest Neighbors, Dimensionality Reduction, Random Forest, K-Means Clustering, and Naive Bayes, understanding what each algorithm actually does, w
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TikTokmohamedibrahembus92
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Everyone talks about LLMs, but traditional machine learning is still winning in many real-world applications. Random Forest, XGBoost, and Gradient Boosted Trees often outperform LLMs for tabular data tasks like customer churn prediction, fraud detection, loan default prediction, and insurance risk analysis. Understanding when to use machine learning instead of an LLM is what separates AI engineers from people chasing hype. Machine Learning, LLM, Random Forest, XGBoost, AI Engineer #techtok #Mach
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TikTokcode_monarch1
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