Udemy - Data Science - Build, Train and Test A Machine Learning M...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 302.7 MB
  • Uploaded By freecoursewb
  • Downloads 140
  • Last checked 3 days ago
  • Date uploaded 3 years ago
  • Seeders 8
  • Leechers 1

Infohash : BDF85A63286DF58230DBA08A45FBC05A53F85043



Data Science: Build, Train & Test A Machine Learning Model



https://DevCourseWeb.com

Last updated 9/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 302.71 MB | Duration: 0h 40m

A practical Hands-on Data Science Project on Graduate Admission Prediction Using Machine Learning

What you'll learn
Using AI and Machine Learning to Predict Chance of Admit into Universities
Building, Training, Testing and Evaluating Machine learning Models
Learn to create heatmaps, correlation tables, scatter plots and distplot using Seaborn library
A-Z step by step guide into importing libraries, importing and exploring datasets, building a Machine learning model, training, testing and evaluating it.
Learn to work with Linear Regression Machine Learning Algorithm to create Machine Learning Models with approx 96 percent accuracy.
Importing, Exploring and Analyzing datasets and finding correlation between its variables

Requirements
Very basic knowledge of python and its libraries

Files:

[ DevCourseWeb.com ] Udemy - Data Science - Build, Train and Test A Machine Learning Model
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Project Overview and Introduction to the Dataset English.srt (8.7 KB)
    • 1 - Project Overview and Introduction to the Dataset.mp4 (24.9 MB)
    • 2 - Introduction to Libraries Linear Regression Algorithm and Colab Platform English.srt (6.4 KB)
    • 2 - Introduction to Libraries Linear Regression Algorithm and Colab Platform.mp4 (26.5 MB)
    2 - Importing Libraries and Dataset
    • 3 - Admission-Predict-Ver1.1.csv (15.8 KB)
    • 3 - Importing all the necessary Libraries and Dataset into the Colab environment English.srt (3.7 KB)
    • 3 - Importing all the necessary Libraries and Dataset into the Colab environment.mp4 (22.4 MB)
    • 4 - Cleaning the Data English.srt (5.2 KB)
    • 4 - Cleaning the Data.mp4 (37.1 MB)
    3 - Exploratory Data Analysis EDA
    • 5 - Exploring the data using Seaborn and Pandas Libraries English.srt (13.2 KB)
    • 5 - Exploring the data using Seaborn and Pandas Libraries.mp4 (104.1 MB)
    4 - Building and Training Machine Learning Model
    • 6 - Build and Train Machine Learning Model English.srt (7.7 KB)
    • 6 - Build and Train Machine Learning Model.mp4 (60.0 MB)
    5 - Model Testing and Evaluation
    • 7 - Google Colab Notebook Code.txt (0.1 KB)
    • 7 - Testing & Evaluating the Performance of the Model English.srt (4.2 KB)
    • 7 - Testing & Evaluating the Performance of the Model.mp4 (27.6 MB)
    • Bonus Resources.txt (0.4 KB)

There are currently no comments. Feel free to leave one :)

Code:

  • udp://tracker.torrent.eu.org:451/announce
  • udp://tracker.tiny-vps.com:6969/announce
  • http://tracker.foreverpirates.co:80/announce
  • udp://tracker.cyberia.is:6969/announce
  • udp://exodus.desync.com:6969/announce
  • udp://explodie.org:6969/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://9.rarbg.to:2780/announce
  • udp://tracker.internetwarriors.net:1337/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://open.stealth.si:80/announce
  • udp://9.rarbg.to:2900/announce
  • udp://9.rarbg.me:2720/announce
  • udp://opentor.org:2710/announce
REVERSE-PROXY 🔄 RP (success) | 1345ms 📄 torrent 🕐 19 Jan 2026, 12:53:33 pm IST ⏰ 13 Feb 2026, 12:53:33 pm IST ✅ Valid for 24d 23h 🔄 Wait 10m