Practical Machine Learning (2024)
Free Download Practical Machine Learning (2024)
Published 1/2024
Created by Michael Chen
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 12 Lectures ( 1h 18m ) | Size: 244 MB
Explore some data. Build data workflows. Build models. Deploy models.
What you'll learn:
Define the roles and responsibilities of a machine learning engineer
Work with datasets using pandas and identify key insights
Leverage data pipeline tools to create data workflows
Train models using libraries like scikit learn, xgboost, and PyTorch
Learn about MLOps and deploy models using backend technology like Triton Inference Server
Requirements:
Some programming or python experience is ideal
Description:
This course is designed for learners from all backgrounds, primarily focusing on beginners. The course covers many of the cornerstones of practical machine learning, including:Industry Use Cases and Employer Expectations: Explore a variety of industry applications for machine learning and understand what companies are looking for in ML roles.Exploring Real-World dаta: Gain hands-on experience with data sourced from a real-world scenario, learning to navigate and interpret complex datasets.Building Data Workflows: Understand the architecture of data pipelines, including typical tools and techniques used in the industry.Model Development and Evaluation: Learn how to construct machine learning models and critically assess their performance and effectiveness. Iterate upon models with feature engineering and hyperparameter tuning.Model Deployment and Monitoring: Master the skills necessary to deploy models into a production environment and continuously monitor their performance.Value to Learners:Applicability of Skills: The skills taught are directly transferable to real-world scenarios, equipping learners with the tools needed for a career in machine learning.Comprehensive Understanding: From data handling to model deployment, this course offers a holistic view of what it takes to be a machine learning engineer.Hands-On Experience: With a focus on practical exercises and real-world examples, learners will gain firsthand experience that goes beyond theoretical knowledge.
Who this course is for:
Software engineers who are interested in machine learning
Python developers who want to dabble in machine learning
Homepage
https://www.udemy.com/course/practical-ml/Rapidgator
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