Python Statistics Essential Training (2023)

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[ DevCourseWeb.com ] Python Statistics Essential Training (2023)
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 01 - Introduction
    • 01 - Being a Python statistics MVP.mp4 (3.4 MB)
    • 01 - Being a Python statistics MVP.srt (1.4 KB)
    • 02 - What you should know.mp4 (998.7 KB)
    • 03 - Using GitHub Codespaces with this course.mp4 (7.8 MB)
    • 03 - Using GitHub Codespaces with this course.srt (5.2 KB)
    02 - 1. Loading and Cleaning Data
    • 01 - Loading data.mp4 (13.3 MB)
    • 01 - Loading data.srt (9.2 KB)
    • 02 - Strings and categories.mp4 (35.7 MB)
    • 02 - Strings and categories.srt (27.1 KB)
    • 03 - Cleaning numbers.mp4 (41.7 MB)
    • 03 - Cleaning numbers.srt (26.7 KB)
    • 04 - Shrinking numbers.mp4 (14.6 MB)
    • 04 - Shrinking numbers.srt (9.4 KB)
    • 05 - Challenge Clean Ames.mp4 (3.2 MB)
    • 05 - Challenge Clean Ames.srt (2.8 KB)
    • 06 - Solution Clean Ames.mp4 (15.0 MB)
    • 06 - Solution Clean Ames.srt (6.3 KB)
    03 - 2. Exploring and Visualizing
    • 01 - Categorical exploration.mp4 (7.7 MB)
    • 01 - Categorical exploration.srt (6.6 KB)
    • 02 - Histograms and distributions.mp4 (8.0 MB)
    • 02 - Histograms and distributions.srt (6.7 KB)
    • 03 - Outliers and Z-scores.mp4 (19.3 MB)
    • 03 - Outliers and Z-scores.srt (10.4 KB)
    • 04 - Correlations.mp4 (26.0 MB)
    • 04 - Correlations.srt (12.3 KB)
    • 05 - Scatter plots.mp4 (15.5 MB)
    • 05 - Scatter plots.srt (12.6 KB)
    • 06 - Visualizing categorical and numerical values.mp4 (25.6 MB)
    • 06 - Visualizing categorical and numerical values.srt (17.1 KB)
    • 07 - Comparing two categoricals.mp4 (13.6 MB)
    • 07 - Comparing two categoricals.srt (10.1 KB)
    • 08 - Challenge Explore Ames.mp4 (802.1 KB)
    • 08 - Challenge Explore Ames.srt (0.7 KB)
    • 09 - Solution Explore Ames.mp4 (6.8 MB)
    • 09 - Solution Explore Ames.srt (5.5 KB)
    04 - 3. Linear Regressions
    • 01 - Linear regression.mp4 (16.7 MB)
    • 01 - Linear regression.srt (13.6 KB)
    • 02 - Interpreting linear regression models.mp4 (10.2 MB)
    • 02 - Interpreting linear regression models.srt (7.4 KB)
    • 03 - Standardizing values.mp4 (19.0 MB)
    • 03 - Standardizing values.srt (10.7 KB)
    • 04 - Regression with XGBoost.mp4 (19.9 MB)
    • 04 - Regression with XGBoost.srt (14.8 KB)
    • 05 - Challenge Predict Ames.mp4 (1.2 MB)
    • 05 - Challenge Predict Ames.srt (1.1 KB)
    • 06 - Solution Predict Ames.mp4 (8.8 MB)
    • 06 - Solution Predict Ames.srt (6.7 KB)
    05 - 4. Hypothesis Tests
    • 01 - Exploring data.mp4 (6.6 MB)
    • 01 - Exploring data.srt (4.8 KB)
    • 02 - Visualizing distributions.mp4 (12.6 MB)
    • 02 - Visualizing distributions.srt (10.3 KB)
    • 03 - Running statistical tests.mp4 (12.7 MB)
    • 03 - Running statistical tests.srt (6.7 KB)
    • 04 - Testing for normality.mp4 (9.7 MB)
    • 04 - Testing for normality.srt (7.3 KB)
    • 05 - Challenge Checking square footage distributions.mp4 (646.9 KB)
    • 05 - Challenge Checking square footage distributions.srt (0.6 KB)
    • 06 - Solution Checking square footage distributions.mp4 (9.2 MB)
    • 06 - Solution Checking square footage distributions.srt (6.3 KB)
    06 - Conclusion
    • 01 - Next steps.mp4 (5.7 MB)
    • 01 - Next steps.srt (2.3 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Python Statistics Essential Training (2023)



https://DevCourseWeb.com

Released 8/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 2h 39m | Size: 392 MB

The field of statistics has become increasingly dependent on data analysis and interpretation using Python. With the rise of big data and data science, the demand for professionals who can effectively analyze and interpret data using Python has skyrocketed. In this course, Matt Harrison teaches you how to collect, clean, analyze, and visualize data using the powerful tools of the Python programming language. Join Matt as he gives into the various techniques that form the backbone of statistics and helps you understand the data with summary statistics and visualizations. He explains how to create predictive models using both linear regression andXGBoost, and wraps up the course with a look at hypothesis testing. If you’re interested in exploring statistics using a code-first approach, join Matt in this course as he shows you how to use Python to unlock the power of data.

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Python Statistics Essential Training (2023)


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392.5 MB
seeders:18
leechers:7
Python Statistics Essential Training (2023)


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