Machine learning explained end to end, from a messy spreadsheet to a trained model that makes real predictions.
Most explanations either stay at the buzzword level or drown you in math. We take the middle path. One housing-price example gets carried from raw data all the way through loss and gradient descent, then the exact same training loop scales up to how ChatGPT is actually built. By the end, the words weights, loss, epochs, tokens, and RLHF stop being jargon and start being one connected idea.
? Try it yourself in the free lab: https://kode.wiki/4gVrsfX
? What you'll learn:
1️⃣ Why if-else rules break on messy problems, and what "learning from examples" replaces them with
2️⃣ What actually changes inside a model when it learns (weights, bias, and the loss that guides them)
3️⃣ How gradient descent, batches, and epochs turn a wrong guess into a good prediction
4️⃣ Why models overfit, and how train/validation/test splits catch it before you ship
5️⃣ How the same loop becomes a neural network, and how GPT gets from next-token prediction to a helpful assistant
? Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX
? Free hands-on lab: https://kode.wiki/4gVrsfX
⏰ Timestamps:
00:00 - Introduction to Machine Learning
00:48 - A Short History of AI and Machine learning
05:25 - What Machine Learning actually is
08:40 - Data, Features, and Labels
12:50 - Lab1: Clean a Messy Housing Dataset
13:37 - Training and Inference
16:00 - Models, Parameters, and Weights
20:13 - Loss functions: Scoring how Wrong the Model is
23:58 - Gradient Descent Explained
28:02 - Lab2: Tune the Model
28:26 - Train, validation, and Test Sets
29:14 - Overfitting and Data Leakage
32:16 - Lab 3: Catch Overfitting and a Data Leak
32:48 - Supervised vs unsupervised learning
36:36 - Classification and Regression
40:00 - Neural Networks Explained
47:20 - How ChatGPT and LLMs are actually Trained
55:58 - Lab4: Train a Neural Network on Handwritten Digits
56:28 - Modern AI: transformers, multimodal, and agents
? Learn AI from this Playlist: https://www.youtube.com/playlist?list=PL2We04F3Y_43f3x3n9pawcEuAwru7bcMG
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