| 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 | ||
| 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 | ||
| 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 | ||
| 6 - Build and Train Machine Learning Model English.srt | 7.7 KB | ||
| 6 - Build and Train Machine Learning Model.mp4 | 60 MB | ||
| 7 - Google Colab Notebook Code.txt | 102.4 B | ||
| 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 | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 18 total files | |||
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
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