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Building Machine Learning Solutions with Python - Code Walkthrough

Offered By: Shaw Talebi via YouTube

Tags

Machine Learning Courses Data Science Courses Python Courses Software Engineering Courses User Interface Design Courses Text Embedding Courses Semantic Search Courses

Course Description

Overview

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Explore the intricacies of building machine learning solutions with Python in this 45-minute video tutorial. Delve into the critical role of experimentation in the ML lifecycle and follow along with a practical code walkthrough for developing a semantic search tool for YouTube videos. Learn about the unique challenges of ML compared to traditional software development, understand design choices for semantic search, and gain hands-on experience with experimentation, evaluation, video indexing, and UI construction. Discover valuable resources and references to deepen your understanding of full-stack data science, RAG, and text embeddings. Perfect for aspiring data scientists and ML practitioners looking to enhance their skills in building real-world ML applications.

Syllabus

Introduction -
Why ML is Different -
Role of Experimentation -
Semantic Search Design Choices -
Example Code: Semantic Search of YT Videos -
Preview of Final Product -
Step 1: Experimentation & Evaluation -
Step 2: Build Video Index -
Step 3: Build UI -
What's Next? -


Taught by

Shaw Talebi

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