Udemy - Machine Learning - Practical labs with Math's Core Foundation

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size906.9 MB
  • Uploaded Byfreecoursewb
  • Downloads57
  • Last checkedSep. 26th '21
  • Date uploadedSep. 24th '21
  • Seeders 6
  • Leechers7

Infohash : C1B17CBDFC38908882E8E7889BA6FD911F20C7C0

Machine Learning: Practical labs with Math's Core Foundation



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 12 lectures (1h 44m) | Size: 602.1 MB
Machine Learning with Mathematics & Python Implementation (Course in progress)
What you'll learn:
Understand the fundamentals of artificial intelligence and machine learning
Describe the methods of machine learning: supervised and unsupervised
Use the data analysis for decision-Making
Understand the limits of algorithms
Understand and grasp Python programming, essential mathematics knowledge in ML, basic programming methods
Knowledge of Calculus, especially derivatives of single variable and multivariate functions
Self-driving cars, Amazon Alexa, Catboats, recommender system, and many more

Requirements
Fundamental knowledge of probability and linear algebra
The ability to code in any computer language, especially in Python language
Knowledge of Calculus, especially derivatives of single variable and multivariate functions

Description
his Machine Learning course provides basic and advanced concepts of machine learning. Our course is designed for students and working professionals.

Machine learning is a growing technology that enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.

Files:

[ TutGator.com ] Udemy - Machine Learning - Practical labs with Math's Core Foundation
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.mp4 (32.7 MB)
    • 1. Introduction.srt (3.0 KB)
    • 1.1 1.pptx (2.2 MB)
    • 2. Curriculum.html (2.4 KB)
    2. Machine Learning Fundamentals
    • 1. Basics of Machine Learning.mp4 (113.3 MB)
    • 1. Basics of Machine Learning.srt (14.3 KB)
    • 1.1 2.pptx (1.5 MB)
    • 2. Applications of Machine Learning.mp4 (119.4 MB)
    • 2. Applications of Machine Learning.srt (11.7 KB)
    • 2.1 2.2 Applications of ML.pdf (584.4 KB)
    • 3. Machine learning Life cycle.mp4 (92.5 MB)
    • 3. Machine learning Life cycle.srt (8.8 KB)
    • 3.1 2.3.pptx (1.1 MB)
    3. Tools for Machine Learning
    • 1. Essential Tools for Machine Learning.mp4 (142.6 MB)
    • 1. Essential Tools for Machine Learning.srt (11.4 KB)
    • 1.1 3.pptx (1.2 MB)
    4. Practical Interaction
    • 1. Installing Anaconda and Python.mp4 (48.0 MB)
    • 1. Installing Anaconda and Python.srt (5.8 KB)
    • 1.1 4.1.pdf (764.0 KB)
    • 1.2 Anaconda Installation.html (0.1 KB)
    • 1.3 Python Installation.html (0.1 KB)
    • 2. How to get datasets for Machine Learning.mp4 (65.6 MB)
    • 2. How to get datasets for Machine Learning.srt (9.9 KB)
    • 2.1 4.2.pdf (639.0 KB)
    • 3. Data Preprocessing in Machine learning.mp4 (161.3 MB)
    • 3. Data Preprocessing in Machine learning.srt (26.0 KB)
    • 3.1 4.3.pdf (698.0 KB)
    • 3.2 data_preprocessing_template.R (0.4 KB)
    • 3.3 data_preprocessing_tools.py (1.4 KB)
    • 3.4 Data.csv (0.2 KB)
    • 3.5 Python Code.html (0.2 KB)
    • 3.6 R Language Code.html (0.2 KB)
    • 4. Supervised Machine Learning.mp4 (66.4 MB)
    • 4. Supervised Machine Learning.srt (6.9 KB)
    • 4.1 4.4.pptx (1.1 MB)
    • 5. Unsupervised Machine Learning.mp4 (53.9 MB)
    • 5. Unsupervised Machine Learning.srt (6.8 KB)
    • 5.1 4.5.pptx (1.1 MB)
    • 6. Section-4 Coding Material.html (0.5 KB)
    • Bonus Resources.txt (0.3 KB)

Code:

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