Udemy - Learn and Implement Machine Learning Projects using Python

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Udemy - Learn and Implement Machine Learning Projects using Python (Size: 3.4 GB)
  1. Basic Concepts.mp4 97.5 MB
  1. Data Visualization using Power BI.mp4 396 MB
  1. How Top Companies Drive Success with Data Science.mp4 53.8 MB
  1. Introduction to Data Visualization.mp4 40 MB
  1. Learn about Federated Machine Learning.mp4 200.2 MB
  1. Python 101 - Basic Python.mp4 467.5 MB
  1. Regression Introduction.mp4 104.5 MB
  1. SQL 101 - Session 1 - Introduction to Database.mp4 11.3 MB
  1. Understanding data.mp4 71.8 MB
  1.1 6 WalmartData.xlsx 16.3 KB
  2. Federated Machine Learning in IoT.mp4 212.5 MB
  2. Important Visualization plots and graphs.mp4 93.8 MB
  2. Machine Learning Models.mp4 120.7 MB
  2. Measure of Central Tendency.mp4 101.3 MB
  2. Overview of Machine Learning.mp4 61.7 MB
  2. Python example of Simple Linear Regression.mp4 105.1 MB
  2. SQL 101 - Session 2 - MYSQL Installation.mp4 23.6 MB
  3. Measure of Variability and use of metric.mp4 104.4 MB
  3. SQL 101 - Session 3 - Launching MYSQL and Creating a database.mp4 20.5 MB
  3. Understanding Regression model evaluation.mp4 77 MB
  3. Understanding the Machine Learning process.mp4 25.8 MB
  3. Whats Artificial Intelligence.mp4 60.2 MB
  4. Artificial intelligence Applications.mp4 115.3 MB
  4. Preprocessing of Dataset.mp4 162.3 MB
  4. SQL 101 - Session 4 - Designing a RDBMS database.mp4 128.9 MB
  5. Learn Data Science Without Any Background.mp4 15 MB
  5. Lecture 12 Running SQL Queries.mp4 320.5 MB
  6. Business Analysts v Data Analyst.mp4 159.5 MB
  7. Data Analytics v Data Scientist.mp4 159.8 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 31 total files

Description


Learn and Implement Machine Learning Projects using Python

https://DevCourseWeb.com

Published 3/2024
Created by Swapnil Saurav
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 28 Lectures ( 7h 39m ) | Size: 3.42 GB

From Basics to Project Deployment: A Practical Python Approach to Machine Learning

What you'll learn:
Foundational ML Concepts: Understand the core principles behind machine learning, including the different types of ML algorithms.
Python for ML: Master the use of Python libraries like NumPy, Pandas, Matplotlib, and Scikit-learn for ML development.
Developing ML Projects: Learn the step-by-step process of creating a machine learning project, from data collection and preprocessing to model training and eval
Real-World Applications: Apply your skills to real-world projects across various domains, such as finance, healthcare, and more.
Model Deployment: Discover how to deploy your machine learning models to production environments.

Requirements:
Familiarity with fundamental programming concepts
A desire to learn and explore the field of machine learning.

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