[ TutGee com ] Udemy - Practical Recommender Systems For Business Applications


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Torrent File Content (56 files)


[ TutGee.com ] Udemy - Practical Recommender Systems For Business Applications
     Get Bonus Downloads Here.url -
176 bytes

    ~Get Your Files Here !
          1. Welcome To The Course/1. What Is the Course About.mp4 -
32.32 MB

          1. Welcome To The Course/2. Data and Code.html -
147 bytes

          1. Welcome To The Course/3. Python Installation.mp4 -
39.29 MB

          1. Welcome To The Course/4. Start With Google Colaboratory Environment.mp4 -
36.71 MB

          1. Welcome To The Course/5. Google Colabs and GPU.mp4 -
27.62 MB

          1. Welcome To The Course/6. Why Recommender Systems.mp4 -
48.85 MB

          2. Basics Of Python For Data Science/1. Introduction to Pandas.mp4 -
69.65 MB

          2. Basics Of Python For Data Science/10. Basic Data Visualisations.mp4 -
28.78 MB

          2. Basics Of Python For Data Science/11. More Visualisations.mp4 -
41.27 MB

          2. Basics Of Python For Data Science/12. Exploring the Temporal Dimension.mp4 -
44.34 MB

          2. Basics Of Python For Data Science/2. Read in Multiple CSVs.mp4 -
49.11 MB

          2. Basics Of Python For Data Science/3. Read in Data From SQL.mp4 -
28.44 MB

          2. Basics Of Python For Data Science/4. Read in JSON Files.mp4 -
35.69 MB

          2. Basics Of Python For Data Science/5. Read in Text Data.mp4 -
11.2 MB

          2. Basics Of Python For Data Science/6. Assess Data Quality.mp4 -
31.93 MB

          2. Basics Of Python For Data Science/7. Python Data Cleaning.mp4 -
31.78 MB

          2. Basics Of Python For Data Science/8. Grouping Data.mp4 -
99.85 MB

          2. Basics Of Python For Data Science/9. More Data Summarisations and Pivoting.mp4 -
77.48 MB

          3. Basic Statistical Concepts/1. Principal Component Analysis (PCA).mp4 -
24.36 MB

          3. Basic Statistical Concepts/10. k-Nearest Neighbours (kNN)-Theory.mp4 -
78.27 MB

          3. Basic Statistical Concepts/2. Practical Application of PCA.mp4 -
26.13 MB

          3. Basic Statistical Concepts/3. Single Vector Decomposition (SVD)-Theory.mp4 -
8.4 MB

          3. Basic Statistical Concepts/4. Implement SVD.mp4 -
15.13 MB

          3. Basic Statistical Concepts/5. Unsupervised Leaning-Theory.mp4 -
28.56 MB

          3. Basic Statistical Concepts/6. K-means Clustering Theory.mp4 -
18.18 MB

          3. Basic Statistical Concepts/7. Cosine Similarity.mp4 -
19.31 MB

          3. Basic Statistical Concepts/8. Jaccard Similarity.mp4 -
6.71 MB

          3. Basic Statistical Concepts/9. Introduction to Supervised Learning.mp4 -
69.74 MB

          4. What Are Recommender Engines/1. Different Types of Recommender System.mp4 -
22.85 MB

          5. Filtering Based Recommender Engines/1. Euclidean Distances as a Basis of Making Recommendations.mp4 -
22.29 MB

          5. Filtering Based Recommender Engines/2. Using Distances and SVD For Recommendations.mp4 -
54.43 MB

          5. Filtering Based Recommender Engines/3. How Demographic Traits Can Help With Making Recommendations.mp4 -
14.14 MB

          5. Filtering Based Recommender Engines/4. Basic Data Processing.mp4 -
39.4 MB

          5. Filtering Based Recommender Engines/5. Final List Of Movies.mp4 -
27.2 MB

          6. Common Recommender Engines/1. Basic Item Based Filtering.mp4 -
25.85 MB

          6. Common Recommender Engines/2. Surprise For More Content Filtering.mp4 -
22.34 MB

          6. Common Recommender Engines/3. Hybrid Recommenders-LightFM.mp4 -
44.03 MB

          6. Common Recommender Engines/4. Set Up a Problem For Classical Recommender Systems.mp4 -
40.46 MB

          6. Common Recommender Engines/5. Content Based Filtering.mp4 -
38.8 MB

          6. Common Recommender Engines/6. Collaborative Filtering.mp4 -
19.86 MB

          7. Working With Text Data/1. Theory of Text Cleaning.mp4 -
58.28 MB

          7. Working With Text Data/2. Text Cleaning-Part 1.mp4 -
24.17 MB

          7. Working With Text Data/3. Text Cleaning-Part 2.mp4 -
27.08 MB

          7. Working With Text Data/4. NTLK-Based Cleaning.mp4 -
34.72 MB

          7. Working With Text Data/5. Another NTLK-Based Workflow.mp4 -
38.97 MB

          7. Working With Text Data/6. What Are Wordclouds.mp4 -
53.08 MB

          7. Working With Text Data/7. Word Clouds For Movie Themes.mp4 -
47.17 MB

          7. Working With Text Data/8. TF-IDF Theory.mp4 -
18.23 MB

          7. Working With Text Data/9. Practical TF-IDF Implementation.mp4 -
22.24 MB



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