Udemy - Complete Data Science Training with Python for Data Analysis [Desire Course]

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[DesireCourse.Net] Udemy - Complete Data Science Training with Python for Data Analysis 1. Introduction to the Data Science in Python Bootcamp
  • 1. What is Data Science.mp4 (17.4 MB)
  • 1. What is Data Science.vtt (4.0 KB)
  • 2. Introduction to the Course Instructor.m4v (55.6 MB)
  • 2. Introduction to the Course Instructor.vtt (13.5 KB)
  • 3. Data For the Course.html (0.1 KB)
  • 3.1 scriptsLecture.zip.zip (308.0 MB)
  • 4. Introduction to the Python Data Science Tool.mp4 (25.0 MB)
  • 4. Introduction to the Python Data Science Tool.vtt (10.1 KB)
  • 5. For Mac Users.mp4 (10.2 MB)
  • 5. For Mac Users.vtt (3.9 KB)
  • 6. Introduction to the Python Data Science Environment.mp4 (40.3 MB)
  • 6. Introduction to the Python Data Science Environment.vtt (17.2 KB)
  • 7. Some Miscellaneous IPython Usage Facts.mp4 (12.0 MB)
  • 7. Some Miscellaneous IPython Usage Facts.vtt (4.5 KB)
  • 8. Online iPython Interpreter.mp4 (7.7 MB)
  • 8. Online iPython Interpreter.vtt (3.4 KB)
  • 9. Conclusion to Section 1.mp4 (6.5 MB)
  • 9. Conclusion to Section 1.vtt (3.1 KB)
10. Unsupervised Learning in Python
  • 1. Unsupervised Classification- Some Basic Ideas.mp4 (6.2 MB)
  • 1. Unsupervised Classification- Some Basic Ideas.vtt (1.8 KB)
  • 10. Principal Component Analysis (PCA)-Practical Implementation.mp4 (9.1 MB)
  • 10. Principal Component Analysis (PCA)-Practical Implementation.vtt (4.2 KB)
  • 11. Conclusions to Section 10.mp4 (5.5 MB)
  • 11. Conclusions to Section 10.vtt (2.5 KB)
  • 2. KMeans-theory.mp4 (5.1 MB)
  • 2. KMeans-theory.vtt (2.5 KB)
  • 3. KMeans-implementation on the iris data.mp4 (19.5 MB)
  • 3. KMeans-implementation on the iris data.vtt (7.6 KB)
  • 4. Quantifying KMeans Clustering Performance.mp4 (9.6 MB)
  • 4. Quantifying KMeans Clustering Performance.vtt (4.4 KB)
  • 5. KMeans Clustering with Real Data.mp4 (12.1 MB)
  • 5. KMeans Clustering with Real Data.vtt (4.5 KB)
  • 6. How Do We Select the Number of Clusters.mp4 (19.0 MB)
  • 6. How Do We Select the Number of Clusters.vtt (4.2 KB)
  • 7. Hierarchical Clustering-theory.mp4 (10.2 MB)
  • 7. Hierarchical Clustering-theory.vtt (5.0 KB)
  • 8. Hierarchical Clustering-practical.mp4 (29.4 MB)
  • 8. Hierarchical Clustering-practical.vtt (9.5 KB)
  • 9. Principal Component Analysis (PCA)-Theory.mp4 (5.9 MB)
  • 9. Principal Component Analysis (PCA)-Theory.vtt (3.0 KB)
11. Supervised Learning
  • 1. What is This Section About.mp4 (24.9 MB)
  • 1. What is This Section About.vtt (11.5 KB)
  • 10. knn-Classification.mp4 (18.2 MB)
  • 10. knn-Classification.vtt (8.0 KB)
  • 11. knn-Regression.mp4 (8.4 MB)
  • 11. knn-Regression.vtt (4.0 KB)
  • 12. Gradient Boosting-classification.mp4 (15.0 MB)
  • 12. Gradient Boosting-classification.vtt (6.0 KB)
  • 13. Gradient Boosting-regression.mp4 (10.9 MB)
  • 13. Gradient Boosting-regression.vtt (3.7 KB)
  • 14. Voting Classifier.mp4 (9.5 MB)
  • 14. Voting Classifier.vtt (3.8 KB)
  • 15. Conclusions to Section 11.mp4 (7.2 MB)
  • 15. Conclusions to Section 11.vtt (2.9 KB)
  • 16. Section 11 Quiz.html (0.2 KB)
  • 2. Data Preparation for Supervised Learning.mp4 (28.3 MB)
  • 2. Data Preparation for Supervised Learning.vtt (10.1 KB)
  • 3. Pointers on Evaluating the Accuracy of Classification and Regression Modelling.mp4 (24.0 MB)
  • 3. Pointers on Evaluating the Accuracy of Classification and Regression Modelling.vtt (10.5 KB)
  • 4. Using Logistic Regression as a Classification Model.mp4 (20.6 MB)
  • 4. Using Logistic Regression as a Classification Model.vtt (8.7 KB)
  • 5. RF-Classification.mp4 (28.5 MB)
  • 5. RF-Classification.vtt (12.2 KB)
  • 6. RF-Regression.mp4 (23.6 MB)
  • 6. RF-Regression.vtt (9.7 KB)
  • 7. SVM- Linear Classification.mp4 (7.4 MB)
  • 7. SVM- Linear Classification.vtt (3.2 KB)
  • 8. SVM- Non Linear Classification.mp4 (5.1 MB)
  • 8. SVM- Non Linear Classification.vtt (2.3 KB)
  • 9. Support Vector Regression.mp4 (10.2 MB)
  • 9. Support Vector Regression.vtt (4.3 KB)
12. Artificial Neural Networks (ANN) and Deep Learning (DL)
  • 1. Theory Behind ANN and DNN.mp4 (22.6 MB)
  • 1. Theory Behind ANN and DNN.vtt (9.9 KB)
  • 10. Specify the Activation Function.mp4 (6.2 MB)
  • 10. Specify the Activation Function.vtt (2.2 KB)
  • 11. H2O Deep Learning For Predictions.mp4 (12.0 MB)
  • 11. H2O Deep Learning For Predictions.vtt (5.2 KB)
  • 12. Conclusions to Section 12.mp4 (5.2 MB)
  • 12. Conclusions to Section 12.vtt (2.1 KB)
  • 13. Section 12 Quiz.html (0.2 KB)
  • 2. Perceptrons for Binary Classification.mp4 (10.0 MB)
  • 2. Perceptrons for Binary Classification.vtt (4.7 KB)
  • 3. Getting Started with ANN-binary classification.mp4 (8.5 MB)
  • 3. Getting Started with ANN-binary classification.vtt (3.5 KB)
  • 4. Multi-label classification with MLP.mp4 (13.5 MB)
  • 4. Multi-label classification with MLP.vtt (4.8 KB)
  • 5. Regression with MLP.mp4 (9.0 MB)
  • 5. Regression with MLP.vtt (3.5 KB)
  • 6. MLP with PCA on a Large Dataset.mp4 (19.2 MB)
  • 6. MLP with PCA on a Large Dataset.vtt (7.6 KB)
  • 7. Start With Deep Neural Network (DNN).html (0.2 KB)
  • 8. Start with H20.mp4 (12.1 MB)
  • 8. Start with H20.vtt (4.3 KB)
  • 9. Default H2O Deep Learning Algorithm.mp4 (8.2 MB)
  • 9. Default H2O Deep Learning Algorithm.vtt (3.4 KB)
13. Miscellaneous Lectures Information
  • 1. Data For This Section.html (0.1 KB)
  • 2. Read in Data from Online CSV.mp4 (6.7 MB)
  • 2. Read in Data from Online CSV.vtt (3.9 KB)
  • 3. Read Data from a Database.mp4 (12.3 MB)
  • 3. Read Data from a Database.vtt (7.8 KB)
  • 4. Naive Bayes Classification.m4v (28.2 MB)
  • 4. Naive Bayes Classification.vtt (6.8 KB)

Description

Complete Data Science Training with Python for Data Analysis

Complete Guide to Practical Data Science with Python: Learn Statistics, Visualization, Machine Learning & More

For More Courses Visit: https://desirecourse.net



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Udemy - Complete Data Science Training with Python for Data Analysis [Desire Course]

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Download torrent
2.3 GB
seeders:13
leechers:14
Udemy - Complete Data Science Training with Python for Data Analysis [Desire Course]

Torrent hash: 6BA6895D7D716420F653594B54E1E102E8CA79AC