Udemy - Machine Learning on Python 2021

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[ CourseHulu.com ] Udemy - Machine Learning on Python 2021
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction to Machine Learning on Python
    • 1. Introduction to Machine Learning.mp4 (57.7 MB)
    • 1. Introduction to Machine Learning.srt (14.9 KB)
    2. Naive Bayes Theory and Application
    • 1. Naive Bayes Theory.mp4 (33.1 MB)
    • 1. Naive Bayes Theory.srt (9.5 KB)
    • 2. Naive Bayes Application in Python.mp4 (22.0 MB)
    • 2. Naive Bayes Application in Python.srt (3.1 KB)
    3. K-Nearest Neighbors (KNN) Theory and Application in Python
    • 1. Application of K-Nearest Neighbors in Python Part-1.mp4 (94.1 MB)
    • 1. Application of K-Nearest Neighbors in Python Part-1.srt (8.4 KB)
    • 2. Application of K-Nearest Neighbors in Python Part-2.mp4 (30.5 MB)
    • 2. Application of K-Nearest Neighbors in Python Part-2.srt (8.5 KB)
    4. Random Forest Theory and Application
    • 1. Random Forest Theory.mp4 (49.7 MB)
    • 1. Random Forest Theory.srt (7.1 KB)
    • 2. Random Forest Application in Python- Part 1.mp4 (77.3 MB)
    • 2. Random Forest Application in Python- Part 1.srt (8.9 KB)
    • 3. Random Forest Application in Python- Part 2.mp4 (33.1 MB)
    • 3. Random Forest Application in Python- Part 2.srt (8.1 KB)
    5. Gradient Boosting Theory and Application
    • 1. Gradient Boosting Theory.mp4 (72.3 MB)
    • 1. Gradient Boosting Theory.srt (11.0 KB)
    • 2. Gradient Boosting Application in Python.mp4 (80.2 MB)
    • 2. Gradient Boosting Application in Python.srt (13.7 KB)
    6. Support Vector Machine Theory and Application in Python
    • 1. Support Vector Machine Theory.mp4 (28.1 MB)
    • 1. Support Vector Machine Theory.srt (7.4 KB)
    • 2. Support Vector Machine Application in Python.mp4 (51.6 MB)
    • 2. Support Vector Machine Application in Python.srt (6.8 KB)
    • Bonus Resources.txt (0.3 KB)

Description

Udemy - Machine Learning on Python 2021



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 12 lectures (1h 41m) | Size: 565.7 MB
A clear understanding about the machine learning theory, techniques and its application in Jupyter Notebook platform
What you'll learn:
A clear understanding about the machine learning theory, techniques and its application in Jupyter Notebook platform.
The program builds a solid foundation by covering the most popular and widely used machine learning technologies and its applications.
Course includes Naive Bayes theory, K Nearest Neighbors (KNN) theory and application, Random forest theory and application, Gradient Boosting Theory etc.
Students will have a good working knowledge on Machine Learning on Python
They can use it for their Educational as well as Business projects and assignments.

Requirements
A knowledge of analytical techniques and their applications on Python

Description
There are people who are eager to move to Analytics careers but do not have the requisite skill sets. As we move into our 12th year in the Analytics Industry, OrangeTree Global has designed specific courses for freshers and working professionals who are looking at moving to Data Science, Machine Learning and Big Data Careers.

Since 2009, OrangeTree Global has embarked on an ambitious vision of providing affordable and effective Analytics Training and Education across the country.



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Udemy - Machine Learning on Python 2021
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