t-SNE Tutorial for Beginners High-Dimensional Data Visualization in Machine Learning

Описание: #tSNE #MachineLearning #DimensionalityReduction #DataScience #Visualization #DeepLearning #Python #ScikitLearn #HighDimensionalDataIn
this video, we will understand t-Distributed Stochastic Neighbor Embedding (t-SNE) — one of the most powerful techniques for visualizing high-dimensional data in Machine Learning.

You will learn:

What is t-SNE?

Why do we use it in ML & Data Science?

How does t-SNE work (intuitive explanation)?

Example with real dataset

Python implementation using Scikit-Learn

Tips to avoid common t-SNE mistakes

Whether you are a Data Scientist, ML beginner, or researcher, this video will help you understand t-SNE clearly with simple explanations and visuals.

🧠 What is t-SNE?

t-SNE (t-Distributed Stochastic Neighbor Embedding) is a non-linear dimensionality reduction technique used to visualize high-dimensional datasets in 2D or 3D. It preserves local structure, making it ideal for clusters like images, text embeddings, or sensor data.