Applied Machine Learning - Algorithms (2024)

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[ DevCourseWeb.com ] Applied Machine Learning - Algorithms (2024)
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 01 - Introduction
    • 01 - Applied machine learning Algorithms.mp4 (4.5 MB)
    • 01 - Applied machine learning Algorithms.srt (1.5 KB)
    • 02 - What you should know.mp4 (4.9 MB)
    • 02 - What you should know.srt (1.9 KB)
    02 - 1. Clustering
    • 01 - K-means.mp4 (18.4 MB)
    • 01 - K-means.srt (14.4 KB)
    • 02 - K evaluation.mp4 (17.8 MB)
    • 02 - K evaluation.srt (13.7 KB)
    • 03 - Understanding clusters.mp4 (19.1 MB)
    • 03 - Understanding clusters.srt (14.9 KB)
    • 04 - Other algorithms.mp4 (5.8 MB)
    • 05 - Challenge Apply KNN.mp4 (1.5 MB)
    • 05 - Challenge Apply KNN.srt (1.5 KB)
    • 06 - Solution Apply KNN.mp4 (15.7 MB)
    • 06 - Solution Apply KNN.srt (12.8 KB)
    03 - 2. PCA
    • 01 - PCA.mp4 (8.3 MB)
    • 01 - PCA.srt (6.3 KB)
    • 02 - Structure of components.mp4 (9.0 MB)
    • 02 - Structure of components.srt (6.5 KB)
    • 03 - Components.mp4 (12.0 MB)
    • 03 - Components.srt (8.7 KB)
    • 04 - Scatter plot.mp4 (4.3 MB)
    • 04 - Scatter plot.srt (3.6 KB)
    • 05 - Other algorithms.mp4 (7.6 MB)
    • 05 - Other algorithms.srt (6.5 KB)
    • 06 - Challenge Utilize PCA.mp4 (933.2 KB)
    • 06 - Challenge Utilize PCA.srt (0.9 KB)
    • 07 - Solution Utilize PCA.mp4 (11.2 MB)
    • 07 - Solution Utilize PCA.srt (6.8 KB)
    04 - 3. Linear Regression
    • 01 - Linear regression algorithm.mp4 (9.6 MB)
    • 01 - Linear regression algorithm.srt (7.5 KB)
    • 02 - scikit-learn.mp4 (8.1 MB)
    • 02 - scikit-learn.srt (7.3 KB)
    • 03 - Real-world example.mp4 (13.3 MB)
    • 03 - Real-world example.srt (9.8 KB)
    • 04 - Assumptions.mp4 (14.4 MB)
    • 04 - Assumptions.srt (10.0 KB)
    • 05 - Challenge Develop a linear regression model.mp4 (1.0 MB)
    • 05 - Challenge Develop a linear regression model.srt (0.8 KB)
    • 06 - Solution Develop a linear regression model.mp4 (4.2 MB)
    • 06 - Solution Develop a linear regression model.srt (3.1 KB)
    05 - 4. Logistic Regression
    • 01 - Logistic regression algorithm.mp4 (2.7 MB)
    • 01 - Logistic regression algorithm.srt (2.2 KB)
    • 02 - Basic example.mp4 (3.6 MB)
    • 02 - Basic example.srt (3.1 KB)
    • 03 - Assumptions.mp4 (9.5 MB)
    • 03 - Assumptions.srt (6.9 KB)
    • 04 - Challenge Construct a logistic regression model.mp4 (360.4 KB)
    • 04 - Challenge Construct a logistic regression model.srt (0.3 KB)
    • 05 - Solution Construct a logistic regression model.mp4 (10.9 MB)
    • 05 - Solution Construct a logistic regression model.srt (7.3 KB)
    06 - 5. Decision Trees
    • 01 - Decision tree algorithm.mp4 (9.0 MB)
    • 01 - Decision tree algorithm.srt (7.3 KB)
    • 02 - Real-world example.mp4 (15.5 MB)
    • 02 - Real-world example.srt (10.9 KB)
    • 03 - Random Forest and XGBoost.mp4 (8.2 MB)
    • 03 - Random Forest and XGBoost.srt (7.6 KB)
    • 04 - Challenge Design a decision tree model.mp4 (713.5 KB)
    • 05 - Solution Design a decision tree model.mp4 (9.0 MB)
    • 05 - Solution Design a decision tree model.srt (5.7 KB)
    07 - Conclusion
    • 01 - Next steps.mp4 (6.6 MB)
    • 01 - Next steps.srt (2.6 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Applied Machine Learning: Algorithms (2024)

https://DevCourseWeb.com

Released 4/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 58m | Size: 268 MB

With the growing importance of machine learning in almost every sector, professionals need a deeper understanding and practical approach to implementing ML algorithms effectively.

This course covers commonly used machine learning algorithms. Instructor Matt Harrison focuses on non-deep learning algorithms, covering PCA, clustering, linear and logistic regression, decision trees, random forests, and gradient boosting.

Join Matt in this course to understand common ML algorithms, learn their pros and cons, and develop hands-on skills to leverage them by following along with challenges and solutions in GitHub Codespaces.



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Applied Machine Learning - Algorithms (2024)


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267.9 MB
seeders:26
leechers:6
Applied Machine Learning - Algorithms (2024)


Torrent hash: 658B92059149FE7BB646258888FEB8D63E4376D8