[FTUForum.com] [UDEMY] Python Machine Learning Basics Shallow Learning Algorithms [FTU]

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Size

451 MB

Seeders

Leechers

Files

Category

Other

Added

05/18/19 at 6:54pm GMT+1

Status

Verified by VeriPLUS

Infohash

aa5bf9d6c42e0f2d108b89824cb50920bf21d9cd

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Description

Become an expert in Python Machine Learning recommendation algorithms

Created by: Mark Nielsen

Last updated: 9/2018

Language: English

Caption (CC): Included

Torrent Contains: 39 Files, 5 Folders

Course Source: https://www.udemy.com/basic-machine-learning-shallow-learning/

What you'll learn

• Understand basic machine learning principles

• Understand the different between Shallow learning and Deep learning

• Implement shallow learning algorithms

Requirements

• Computer

• Internet

• No prior coding knowledge

Description

Start your Machine Learning career with this basic Machine learning course. Together we will look into the "shallow" learning algorithms KNN and SVD. The course consist of both assignments, follow along programming and theory lectures to ensure that you as a student have the best possible foundation to make real world applications using KNN or SVD.

Who this course is for:

• Anyone who wish to learn machine learning

• Anyone who wish to develop recommender systems.

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File list

[FTUForum.com] [UDEMY] Python Machine Learning Basics Shallow Learning Algorithms [FTU]
0. Websites you may like/How you can help Team-FTU.txt 237 B
1. Introduction/1. What is Machine Learning.mp4 28.7 MB
1. Introduction/1. What is Machine Learning.vtt 5.8 KB
1. Introduction/2. Shallow vs Deep learning.mp4 13.3 MB
1. Introduction/2. Shallow vs Deep learning.vtt 3.4 KB
1. Introduction/3. Theory vs Practice.mp4 11.4 MB
1. Introduction/3. Theory vs Practice.vtt 3.6 KB
2. Machine Learning Framework/1. Scikit Surprise.mp4 38.6 MB
2. Machine Learning Framework/1. Scikit Surprise.vtt 4.4 KB
2. Machine Learning Framework/2. Evaluation.mp4 21.5 MB
2. Machine Learning Framework/2. Evaluation.vtt 8 KB
2. Machine Learning Framework/3. Install Python 3.5+.mp4 7.3 MB
2. Machine Learning Framework/3. Install Python 3.5+.vtt 1017 B
2. Machine Learning Framework/4. MI Python skeleton.mp4 58.7 MB
2. Machine Learning Framework/4. MI Python skeleton.vtt 8.9 KB
3. SVD/1. SVD implementation.mp4 53.1 MB
3. SVD/1. SVD implementation.vtt 6.9 KB
3. SVD/2. SVD Theory.mp4 37 MB
3. SVD/2. SVD Theory.vtt 4.5 KB
3. SVD/2.1 Singular Value Decomposition Stanford University.html 104 B
3. SVD/3. Implement SVD().html 150 B
4. KNN/1. KNN implementation.mp4 37.7 MB
4. KNN/1. KNN implementation.vtt 4.2 KB
4. KNN/2. Knn theory.mp4 22.6 MB
4. KNN/2. Knn theory.vtt 5.6 KB
4. KNN/3. User vs Item.mp4 18.6 MB
4. KNN/3. User vs Item.vtt 2.3 KB
4. KNN/4. Implementing KNN.html 150 B
5. Going Live/1. Display KNN neighbors.mp4 31.7 MB
5. Going Live/1. Display KNN neighbors.vtt 4.1 KB
5. Going Live/2. Display SVD Item Predictions.mp4 22.6 MB
5. Going Live/2. Display SVD Item Predictions.vtt 3.9 KB
5. Going Live/3. Surpriselib and Flask.mp4 48.5 MB
5. Going Live/3. Surpriselib and Flask.vtt 6.1 KB

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