Udemy - Data Science with Python

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[FreeCourseLab.com] Udemy - Data Science with Python 1. Introduction
  • 1. Introduction to Data Visualization.mp4 (17.0 MB)
  • 1. Introduction to Data Visualization.vtt (4.8 KB)
2. What is Data Science
  • 1. Understanding Data Science.mp4 (18.0 MB)
  • 1. Understanding Data Science.vtt (5.8 KB)
  • 2. Python Environment Framework.mp4 (27.5 MB)
  • 2. Python Environment Framework.vtt (4.9 KB)
  • 3. Various Python Scripts.mp4 (28.7 MB)
  • 3. Various Python Scripts.vtt (6.4 KB)
3. Advanced Python
  • 1. Concept of Advanced Python.mp4 (26.5 MB)
  • 1. Concept of Advanced Python.vtt (6.2 KB)
  • 2. Creating Functions for Python.mp4 (23.6 MB)
  • 2. Creating Functions for Python.vtt (4.4 KB)
  • 3. Creating a New Library.mp4 (22.8 MB)
  • 3. Creating a New Library.vtt (4.7 KB)
  • 4. Creating Bar Charts.mp4 (39.0 MB)
  • 4. Creating Bar Charts.vtt (7.6 KB)
  • 5. Analysis on Line Chart.mp4 (30.3 MB)
  • 5. Analysis on Line Chart.vtt (5.6 KB)
  • 6. Understanding Scattered Plots.mp4 (35.1 MB)
  • 6. Understanding Scattered Plots.vtt (5.7 KB)
4. Linear Algebra
  • 1. Vector Spaces in Linear Algebra.mp4 (35.4 MB)
  • 1. Vector Spaces in Linear Algebra.vtt (6.4 KB)
  • 2. Matrices in Linear Algebra.mp4 (53.0 MB)
  • 2. Matrices in Linear Algebra.vtt (10.0 KB)
  • 3. Analysing Statistical Data.mp4 (29.1 MB)
  • 3. Analysing Statistical Data.vtt (6.0 KB)
  • 4. Understanding Central Tendencies.mp4 (63.0 MB)
  • 4. Understanding Central Tendencies.vtt (9.8 KB)
  • 5. Dispersion for Data.mp4 (34.3 MB)
  • 5. Dispersion for Data.vtt (5.3 KB)
5. Probability
  • 1. Probability in Discreet Mathematics.mp4 (20.6 MB)
  • 1. Probability in Discreet Mathematics.vtt (4.3 KB)
  • 10. Line of Best Fit.mp4 (30.6 MB)
  • 10. Line of Best Fit.vtt (4.3 KB)
  • 11. Datascience with Gradient Descent.mp4 (13.8 MB)
  • 11. Datascience with Gradient Descent.vtt (3.7 KB)
  • 12. Example on Gradient Descent.mp4 (31.7 MB)
  • 12. Example on Gradient Descent.vtt (4.8 KB)
  • 2. Normal Distribution Curve.mp4 (43.7 MB)
  • 2. Normal Distribution Curve.vtt (6.7 KB)
  • 3. Example for Normal Distribution Curve.mp4 (32.5 MB)
  • 3. Example for Normal Distribution Curve.vtt (5.1 KB)
  • 4. Central Limit Theorem.mp4 (36.8 MB)
  • 4. Central Limit Theorem.vtt (6.2 KB)
  • 5. Concept of Hypothesis.mp4 (26.2 MB)
  • 5. Concept of Hypothesis.vtt (4.1 KB)
  • 6. Example on Hypothesis Testing.mp4 (49.3 MB)
  • 6. Example on Hypothesis Testing.vtt (6.5 KB)
  • 7. Defining the Next Value.mp4 (59.6 MB)
  • 7. Defining the Next Value.vtt (7.6 KB)
  • 8. Principle of P Hacking.mp4 (27.4 MB)
  • 8. Principle of P Hacking.vtt (4.3 KB)
  • 9. Understanding Bayesian Inference.mp4 (27.9 MB)
  • 9. Understanding Bayesian Inference.vtt (5.1 KB)
6. Gradient Descent
  • 1. Value Import.mp4 (58.8 MB)
  • 1. Value Import.vtt (6.1 KB)
  • 2. Output Functions for Gradient.mp4 (51.7 MB)
  • 2. Output Functions for Gradient.vtt (5.5 KB)
  • 3. Working with Data Analysis.mp4 (56.2 MB)
  • 3. Working with Data Analysis.vtt (8.4 KB)
  • 4. Creating Normal Histogram.mp4 (65.0 MB)
  • 4. Creating Normal Histogram.vtt (6.4 KB)
  • 5. Two Dimensional Graph.mp4 (49.1 MB)
  • 5. Two Dimensional Graph.vtt (5.6 KB)
  • 6. Multiple Scatter Plots.mp4 (45.5 MB)
  • 6. Multiple Scatter Plots.vtt (6.0 KB)
  • 7. Analyzing Data Sets.mp4 (34.6 MB)
  • 7. Analyzing Data Sets.vtt (5.5 KB)
  • 8. Learnig Box Plots.mp4 (39.9 MB)
  • 8. Learnig Box Plots.vtt (5.6 KB)
7. Conclusion
  • 1. Overview and Conclusion.mp4 (13.0 MB)
  • 1. Overview and Conclusion.vtt (4.0 KB)
  • [FreeCourseLab.com].url (0.1 KB)

Description

Udemy - Data Science with Python



Data visualization is understanding the significance of data by placing it in a visual context. Patterns, trends that might go unnoticed in text-based data can be exposed and recognized easier with data visualization software. It basically involves presentation of data in a pictorial or graphical format.

Through this training we are going to learn how to use Python to create fascinating data visualizations.

The training includes the following;

1. Introduction to Data Visualization

2. Development Setup

3. Language Learning Bridge between Python and JS

4. Reading and Writing Data with Python

5. Webdev 101



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1.3 GB
seeders:15
leechers:13
Udemy - Data Science with Python
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