[ FreeCourseWeb ] Udemy - Machine Learning with SciKit-Learn with Python

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[ FreeCourseWeb.com ] Udemy - Machine Learning with SciKit-Learn with Python
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction to Machine Learning.mp4 (27.8 MB)
    • 1. Introduction to Machine Learning.srt (7.5 KB)
    • 2. Advantages and Disadvantages of Machine Learning.mp4 (26.9 MB)
    • 2. Advantages and Disadvantages of Machine Learning.srt (10.9 KB)
    10. Movie Review Analysis
    • 1. Movie Review Screen Stream.mp4 (67.8 MB)
    • 1. Movie Review Screen Stream.srt (11.1 KB)
    • 2. Movie Review Screen Stream Continue.mp4 (37.6 MB)
    • 2. Movie Review Screen Stream Continue.srt (5.3 KB)
    2. NumPy
    • 1. NumPy Introduction.mp4 (35.8 MB)
    • 1. NumPy Introduction.srt (9.6 KB)
    • 2. Features and Installation.mp4 (56.8 MB)
    • 2. Features and Installation.srt (8.5 KB)
    3. NumPy Array
    • 1. NumPy Array Creation.mp4 (55.2 MB)
    • 1. NumPy Array Creation.srt (12.5 KB)
    • 10. Copies and Views.mp4 (56.1 MB)
    • 10. Copies and Views.srt (7.6 KB)
    • 2. NumPy Array Attributes.mp4 (56.0 MB)
    • 2. NumPy Array Attributes.srt (9.8 KB)
    • 3. NumPy Array Operations.mp4 (78.5 MB)
    • 3. NumPy Array Operations.srt (14.3 KB)
    • 4. NumPy Array Operations Continue.mp4 (93.0 MB)
    • 4. NumPy Array Operations Continue.srt (14.3 KB)
    • 5. NumPy Array Unary Operations.mp4 (35.5 MB)
    • 5. NumPy Array Unary Operations.srt (6.8 KB)
    • 6. Numpy Array Splicing.mp4 (98.8 MB)
    • 6. Numpy Array Splicing.srt (14.2 KB)
    • 7. NumPy Array Shpe.mp4 (67.3 MB)
    • 7. NumPy Array Shpe.srt (13.8 KB)
    • 8. Stacking Together Different Arrays.mp4 (85.5 MB)
    • 8. Stacking Together Different Arrays.srt (11.4 KB)
    • 9. Splitting one Array into Several Smaller ones.mp4 (43.7 MB)
    • 9. Splitting one Array into Several Smaller ones.srt (8.1 KB)
    4. Indexing Arrays of Arrays
    • 1. NumPy Array Indexing.mp4 (61.8 MB)
    • 1. NumPy Array Indexing.srt (12.0 KB)
    • 2. NumPy Array Indexing Continue.mp4 (35.4 MB)
    • 2. NumPy Array Indexing Continue.srt (6.2 KB)
    • 3. NumPy Array Boolean.mp4 (66.9 MB)
    • 3. NumPy Array Boolean.srt (12.5 KB)
    5. Matlplotlib
    • 1. Introduction to Matlplotlib.mp4 (27.5 MB)
    • 1. Introduction to Matlplotlib.srt (5.9 KB)
    • 2. Understanding Various Functions of Pyplot.mp4 (85.4 MB)
    • 2. Understanding Various Functions of Pyplot.srt (13.8 KB)
    • 3. Multiple Figures and Subplots.mp4 (110.3 MB)
    • 3. Multiple Figures and Subplots.srt (13.9 KB)
    6. Pandas
    • 1. Intro to Pandas.mp4 (37.5 MB)
    • 1. Intro to Pandas.srt (10.5 KB)
    • 2. Intro to Pandas Continue.mp4 (42.6 MB)
    • 2. Intro to Pandas Continue.srt (11.2 KB)
    • 3. Data Structure in Pandas.mp4 (83.9 MB)
    • 3. Data Structure in Pandas.srt (12.1 KB)
    • 4. Data Structure in Pandas Continue.mp4 (102.2 MB)
    • 4. Data Structure in Pandas Continue.srt (16.4 KB)
    • 5. Pandas Column Select.mp4 (79.6 MB)
    • 5. Pandas Column Select.srt (13.3 KB)
    • 6. Remove Operations.mp4 (117.4 MB)
    • 6. Remove Operations.srt (11.3 KB)
    • 7. Pandas Arithmetic Operations.mp4 (103.2 MB)
    • 7. Pandas Arithmetic Operations.srt (14.1 KB)
    • 8. Pandas Arithmetic Operations Continue.mp4 (49.7 MB)
    • 8. Pandas Arithmetic Operations Continue.srt (8.6 KB)
    7. Scikit Learn
    • 1. Introduction to Scikit Learn.mp4 (48.8 MB)
    • 1. Introduction to Scikit Learn.srt (12.0 KB)
    • 2. Supervised.mp4 (52.5 MB)
    • 2. Supervised.srt (13.3 KB)
    • 3. Unsupervised Learning.mp4 (53.3 MB)
    • 3. Unsupervised Learning.srt (10.7 KB)
    • 4. Load Data Set.mp4 (43.4 MB)
    • 4. Load Data Set.srt (7.9 KB)
    8. Learning and Predicting
    • 1. Scikit Example Digits.mp4 (45.2 MB)
    • 1. Scikit Example Digits.srt (10.3 KB)
    • 2. Digits Dataset Using Matplotlib.mp4 (62.8 MB)
    • 2. Digits Dataset Using Matplotlib.srt (9.6 KB)
    • 3. Understading Metrics of Predicted Digits Dataset.mp4 (42.0 MB)
    • 3. Understading Metrics of Predicted Digits Dataset.srt (8.0 KB)
    • 4. Persisting Models.mp4 (105.2 MB)
    • 4. Persisting Models.srt (17.7 KB)
    • 5. K-NN Algorithm with Example.mp4 (101.4 MB)
    • 5. K-NN Algorithm with Example.srt (20.3 KB)
    9. Cross Validation
    • 1. Cross Validation.mp4 (112.0 MB)
    • 1. Cross Validation.srt (17.6 KB)
    • 10. Extracting Features.mp4 (46.9 MB)
    • 10. Extracting Features.srt (9.4 KB)
    • 11. Occurrences to Frequencies.mp4 (77.1 MB)
    • 11. Occurrences to Frequencies.srt (12.8 KB)
    • 12. Classifier Training.mp4 (61.0 MB)
    • 12. Classifier Training.srt (8.1 KB)
    • 13. Performance Analysis on the Test Set.mp4 (119.4 MB)
    • 13. Performance Analysis on the Test Set.srt (15.3 KB)
    • 14. Parameter Tuning.mp4 (85.1 MB)
    • 14. Parameter Tuning.srt (13.4 KB)
    • 15. Language Identifcation.mp4 (92.9 MB)
    • 15. Language Identifcation.srt (17.8 KB)
    • 2. Cross Validation Techniques.mp4 (52.2 MB)
    • 2. Cross Validation Techniques.srt (8.9 KB)
    • 3. K-Means Clustering Example.mp4 (104.0 MB)
    • 4. Agglomeration.mp4 (76.6 MB)
    • 4. Agglomeration.srt (12.8 KB)
    • 5. PCA Pipeline.mp4 (117.2 MB)
    • 5. PCA Pipeline.srt (19.2 KB)
    • 6. Face Recognition.mp4 (53.6 MB)
    • 6. Face Recognition.srt (8.6 KB)
    • 7. Face Recognition Output.mp4 (52.1 MB)
    • 8. Right Estimator.mp4 (59.9 MB)
    • 8. Right Estimator.srt (9.0 KB)
    • 9. Text Data Example.mp4 (89.8 MB)
    • 9. Text Data Example.srt (16.2

Description

Udemy- Machine Learning with SciKit-Learn with Python



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 54 lectures (8 hour, 23 mins) | Size: 3.59 GB
Get a practical understanding of the Scikit-Learn library and learn the ML implementation
What you'll learn

This Scikit-learn Training has been designed in a manner so that it can contain all the topics that the trainees have to expertise so that they can work effectively with this library. At the starting of the course, you will get to learn about Machine Learning with SciKit-Learn which is one of the important components of this course where you will be learning every single thing about SciKit-Learn.
You will be getting deep exposure to python in this training. Once you are done with this course, you will be possessing an ample skillset to work efficiently with the SciKit-Learn library.

Requirements

Several topics or concepts are there for which you should have a basic understanding of to make the learning of this library easy for you. The very first thing is the basics of python. As this library is entirely based on python, the trainees need to have a basic understanding of the concepts of python. If you would have worked with python, you will find the concepts covered here pretty simple.
The next important concept is the basics of Machine learning. With the help of this library, we will be implementing the concepts of ML. So it is very necessary to understand how it could be used. In this Scikit-learn Training, we have included all the topics that we are considering as the prerequisite here so that the trainees can brush up their understanding before beginning this training.

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[ FreeCourseWeb ] Udemy - Machine Learning with SciKit-Learn with Python

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3.6 GB
seeders:12
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[ FreeCourseWeb ] Udemy - Machine Learning with SciKit-Learn with Python

Torrent hash: 4B45E879EB2FA6B6A434D86138207F0104D565A6