[FreeCourseSite.com] Udemy - Python for Machine Learning The Complete Beginner's Course

File Type Create Time File Size Seeders Leechers Updated
Movie 2024-01-20 544.43MB 6 0 3 months ago
Download
Magnet link   or   Save Instantly without Torrenting   or   Torrent download

To download this file, you need a free bitTorrent client such as qBittorrent.

Report Abuse
Tags
FreeCourseSite  com  Udemy  Python  for  Machine  Learning  The  Complete  Beginner  Course  
Related Torrents
  1. [FreeCourseSite.com] Udemy - Python for Machine Learning with Numpy, Pandas & Matplotlib 1.39GB
  2. FreeCourseSite.com-Udemy - 100 Days of Code The Complete Python Pro Bootcamp for 2023.torrent 300.36KB
  3. [FreeCourseSite.com] Udemy - 100 Days of Code The Complete Python Pro Bootcamp for 2022 35.95GB
  4. [FreeCourseSite.com] Udemy - 100 Days of Code The Complete Python Pro Bootcamp for 2023.zip 32.36GB
  5. [FreeCourseSite.com] Udemy - NgRx (with NgRx Data) - The Complete Guide (Angular 16) 1.92GB
  6. [ DevCourseWeb.com ] Udemy - ChatGPT for content creation - The complete 2023 edition 3.30GB
  7. Udemy - Python For Offensive PenTest - A Complete Practical Course 1.25GB
  8. [FreeCourseSite.com] Udemy - Python-Introduction to Data Science and Machine learning A-Z 3.20GB
  9. [GigaCourse.Com] Udemy - 2022 Python for Machine Learning & Data Science Masterclass 16.31GB
  10. [ DevCourseWeb.com ] Udemy - Fast-Track Machine Learning in Python and ChatGPT 1.74GB
Files
  1. 1. Introduction to Machine Learning/1. What is Machine Learning.mp4 5.00MB
  2. 1. Introduction to Machine Learning/2. Applications of Machine Learning.mp4 5.52MB
  3. 1. Introduction to Machine Learning/3. Machine learning Methods.mp4 3.70MB
  4. 1. Introduction to Machine Learning/3. Machine learning Methods.srt 437B
  5. 1. Introduction to Machine Learning/4. What is Supervised learning.mp4 5.31MB
  6. 1. Introduction to Machine Learning/5. What is Unsupervised learning.mp4 5.08MB
  7. 1. Introduction to Machine Learning/6. Supervised learning vs Unsupervised learning.mp4 13.12MB
  8. 1. Introduction to Machine Learning/7.14 u.data 1.98MB
  9. 1. Introduction to Machine Learning/7.15 user data.csv 10.67KB
  10. 1. Introduction to Machine Learning/7.2 Decision_tree.ipynb 14.31KB
  11. 1. Introduction to Machine Learning/7.3 homeprices.csv 77B
  12. 1. Introduction to Machine Learning/7.4 K-means algorithm numpy&pandas clustering.ipynb 102.34KB
  13. 1. Introduction to Machine Learning/7.5 KNN_Binary_Classification.ipynb 25.20KB
  14. 1. Introduction to Machine Learning/7.6 linear_regression_houseprice.ipynb 16.34KB
  15. 1. Introduction to Machine Learning/7.7 logistic_regression_Binary_Classification.ipynb 2.74KB
  16. 1. Introduction to Machine Learning/7.8 mall customers data.csv 4.28KB
  17. 1. Introduction to Machine Learning/7.9 mallCustomerData.txt 3.89KB
  18. 2. Simple Linear Regression/1. Introduction to regression.mp4 8.97MB
  19. 2. Simple Linear Regression/1. Introduction to regression.srt 1.86KB
  20. 2. Simple Linear Regression/2. How Does Linear Regression Work.mp4 487.16KB
  21. 2. Simple Linear Regression/4. Implementation in python Importing libraries & datasets.mp4 7.55MB
  22. 2. Simple Linear Regression/4. Implementation in python Importing libraries & datasets.srt 1.44KB
  23. 2. Simple Linear Regression/5. Implementation in python Distribution of the data.mp4 7.79MB
  24. 2. Simple Linear Regression/6. Implementation in python Creating a linear regression object.mp4 13.22MB
  25. 2. Simple Linear Regression/6. Implementation in python Creating a linear regression object.srt 2.83KB
  26. 3. Multiple Linear Regression/1. Understanding Multiple linear regression.mp4 6.10MB
  27. 3. Multiple Linear Regression/2. Implementation in python Exploring the dataset.mp4 9.78MB
  28. 3. Multiple Linear Regression/3. Implementation in python Encoding Categorical Data.mp4 27.46MB
  29. 3. Multiple Linear Regression/4. Implementation in python Splitting data into Train and Test Sets.mp4 8.83MB
  30. 3. Multiple Linear Regression/4. Implementation in python Splitting data into Train and Test Sets.srt 1.52KB
  31. 3. Multiple Linear Regression/5. Implementation in python Training the model on the Training set.mp4 715.56KB
  32. 3. Multiple Linear Regression/6. Implementation in python Predicting the Test Set results.mp4 17.83MB
  33. 3. Multiple Linear Regression/6. Implementation in python Predicting the Test Set results.srt 2.85KB
  34. 3. Multiple Linear Regression/7. Evaluating the performance of the regression model.mp4 5.25MB
  35. 3. Multiple Linear Regression/8. Root Mean Squared Error in Python.mp4 11.83MB
  36. 3. Multiple Linear Regression/8. Root Mean Squared Error in Python.srt 2.25KB
  37. 4. Classification Algorithms K-Nearest Neighbors/1. Introduction to classification.mp4 417.76KB
  38. 4. Classification Algorithms K-Nearest Neighbors/10. Implementation in python Results prediction & Confusion matrix.mp4 9.67MB
  39. 4. Classification Algorithms K-Nearest Neighbors/10. Implementation in python Results prediction & Confusion matrix.srt 1.39KB
  40. 4. Classification Algorithms K-Nearest Neighbors/2. K-Nearest Neighbors algorithm.mp4 3.06MB
  41. 4. Classification Algorithms K-Nearest Neighbors/3. Example of KNN.mp4 3.01MB
  42. 4. Classification Algorithms K-Nearest Neighbors/4. K-Nearest Neighbours (KNN) using python.mp4 5.53MB
  43. 4. Classification Algorithms K-Nearest Neighbors/5. Implementation in python Importing required libraries.mp4 5.11MB
  44. 4. Classification Algorithms K-Nearest Neighbors/5. Implementation in python Importing required libraries.srt 434B
  45. 4. Classification Algorithms K-Nearest Neighbors/6. Implementation in python Importing the dataset.mp4 8.28MB
  46. 4. Classification Algorithms K-Nearest Neighbors/7. Implementation in python Splitting data into Train and Test Sets.mp4 14.98MB
  47. 4. Classification Algorithms K-Nearest Neighbors/8. Implementation in python Feature Scaling.mp4 3.29MB
  48. 4. Classification Algorithms K-Nearest Neighbors/9. Implementation in python Importing the KNN classifier.mp4 7.56MB
  49. 5. Classification Algorithms Decision Tree/1. Introduction to decision trees.mp4 5.05MB
  50. 5. Classification Algorithms Decision Tree/2. What is Entropy.mp4 3.56MB
  51. 5. Classification Algorithms Decision Tree/3. Exploring the dataset.mp4 5.96MB
  52. 5. Classification Algorithms Decision Tree/3. Exploring the dataset.srt 1.33KB
  53. 5. Classification Algorithms Decision Tree/4. Decision tree structure.mp4 6.39MB
  54. 5. Classification Algorithms Decision Tree/4. Decision tree structure.srt 1.33KB
  55. 5. Classification Algorithms Decision Tree/5. Implementation in python Importing libraries & datasets.mp4 2.99MB
  56. 5. Classification Algorithms Decision Tree/6. Implementation in python Encoding Categorical Data.mp4 13.34MB
  57. 5. Classification Algorithms Decision Tree/7. Implementation in python Splitting data into Train and Test Sets.mp4 4.92MB
  58. 5. Classification Algorithms Decision Tree/7. Implementation in python Splitting data into Train and Test Sets.srt 879B
  59. 5. Classification Algorithms Decision Tree/8. Implementation in python Results prediction & Accuracy.mp4 4.43MB
  60. 6. Classification Algorithms Logistic regression/1. Introduction.mp4 6.59MB
  61. 6. Classification Algorithms Logistic regression/1. Introduction.srt 1.42KB
  62. 6. Classification Algorithms Logistic regression/2. Implementation steps.mp4 4.39MB
  63. 6. Classification Algorithms Logistic regression/3. Implementation in python Importing libraries & datasets.mp4 6.82MB
  64. 6. Classification Algorithms Logistic regression/3. Implementation in python Importing libraries & datasets.srt 1.85KB
  65. 6. Classification Algorithms Logistic regression/4. Implementation in python Splitting data into Train and Test Sets.mp4 7.08MB
  66. 6. Classification Algorithms Logistic regression/5. Implementation in python Pre-processing.mp4 9.90MB
  67. 6. Classification Algorithms Logistic regression/6. Implementation in python Training the model.mp4 7.72MB
  68. 6. Classification Algorithms Logistic regression/7. Implementation in python Results prediction & Confusion matrix.mp4 13.46MB
  69. 6. Classification Algorithms Logistic regression/7. Implementation in python Results prediction & Confusion matrix.srt 2.52KB
  70. 6. Classification Algorithms Logistic regression/8. Logistic Regression vs Linear Regression.mp4 10.76MB
  71. 6. Classification Algorithms Logistic regression/8. Logistic Regression vs Linear Regression.srt 2.86KB
  72. 7. Clustering/1. Introduction to clustering.mp4 2.67MB
  73. 7. Clustering/10. Importing the dataset.mp4 11.41MB
  74. 7. Clustering/11. Visualizing the dataset.mp4 7.62MB
  75. 7. Clustering/12. Defining the classifier.mp4 6.19MB
  76. 7. Clustering/13. 3D Visualization of the clusters.mp4 7.82MB
  77. 7. Clustering/13. 3D Visualization of the clusters.srt 1.59KB
  78. 7. Clustering/14. 3D Visualization of the predicted values.mp4 12.71MB
  79. 7. Clustering/15. Number of predicted clusters.mp4 2.87MB
  80. 7. Clustering/2. Use cases.mp4 4.05MB
  81. 7. Clustering/2. Use cases.srt 1024B
  82. 7. Clustering/3. K-Means Clustering Algorithm.mp4 5.32MB
  83. 7. Clustering/4. Elbow method.mp4 4.70MB
  84. 7. Clustering/5. Steps of the Elbow method.mp4 4.68MB
  85. 7. Clustering/6. Implementation in python.mp4 15.84MB
  86. 7. Clustering/7. Hierarchical clustering.mp4 4.84MB
  87. 7. Clustering/8. Density-based clustering.mp4 6.42MB
  88. 8. Recommender System/1. Introduction.mp4 4.69MB
  89. 8. Recommender System/10. Data pre-processing.mp4 10.76MB
  90. 8. Recommender System/10. Data pre-processing.srt 2.19KB
  91. 8. Recommender System/11. Sorting the most-rated movies.mp4 6.39MB
  92. 8. Recommender System/13. Correlation between the most-rated movies.mp4 13.03MB
  93. 8. Recommender System/14. Sorting the data by correlation.mp4 2.74MB
  94. 8. Recommender System/15. Filtering out movies.mp4 1.60MB
  95. 8. Recommender System/17. Repeating the process for another movie.mp4 12.66MB
  96. 8. Recommender System/17. Repeating the process for another movie.srt 2.54KB
  97. 8. Recommender System/18. Quiz Time.html 188B
  98. 8. Recommender System/2. Collaborative Filtering in Recommender Systems.mp4 4.16MB
  99. 8. Recommender System/2. Collaborative Filtering in Recommender Systems.srt 674B
  100. 8. Recommender System/3. Content-based Recommender System.mp4 1.14MB
  101. 8. Recommender System/4. Implementation in python Importing libraries & datasets.mp4 9.27MB
  102. 8. Recommender System/5. Merging datasets into one dataframe.mp4 2.00MB
  103. 8. Recommender System/6. Sorting by title and rating.mp4 18.81MB
  104. 8. Recommender System/7. Histogram showing number of ratings.mp4 4.47MB
  105. 8. Recommender System/8. Frequency distribution.mp4 6.05MB
  106. 8. Recommender System/8. Frequency distribution.srt 1.25KB
  107. 8. Recommender System/9. Jointplot of the ratings and number of ratings.mp4 6.75MB
  108. 9. Conclusion/1. Conclusion.mp4 2.80MB
  109. 9. Conclusion/1. Conclusion.srt 414B