Udemy - Master Python using ChatGPT

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[ DevCourseWeb.com ] Udemy - Master Python using ChatGPT
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Course Introduction and Key Learning Outcomes.mp4 (9.3 MB)
    • 1.1 Introduction and key learning outcomes.pptx (372.6 KB)
    • 2. ChatGPT Introduction.mp4 (26.4 MB)
    • 3. ChatGPT Practical.mp4 (18.0 MB)
    2. Python
    • 1. Data Types and Variables.mp4 (38.2 MB)
    • 2. User Input.mp4 (12.5 MB)
    • 3. Lists.mp4 (36.4 MB)
    • 4. Conditional Statements.mp4 (19.7 MB)
    • 5. Loops.mp4 (27.8 MB)
    3. Numpy
    • 1. Introduction and Installation.mp4 (36.0 MB)
    • 1.1 Numpy Introduction and Installation.ipynb (1.6 KB)
    • 2. Create a Numpy Array.mp4 (53.0 MB)
    • 2.1 Creating Arrays Numpy.ipynb (4.5 KB)
    • 3. Shape and Reshape.mp4 (50.1 MB)
    • 4. Indexing.mp4 (35.8 MB)
    • 4.1 Array Indexing.ipynb (4.0 KB)
    • 5. Iterating.mp4 (25.8 MB)
    • 5.1 Array Iterating Practical.ipynb (2.1 KB)
    • 6. Slicing.mp4 (43.2 MB)
    • 6.1 Array Slicing.ipynb (4.3 KB)
    • 7. Searching and Sorting.mp4 (32.7 MB)
    • 7.1 Searching and Sorting numpy array prac.ipynb (3.9 KB)
    4. Pandas
    • 1. Pandas Introduction and Installation.mp4 (26.1 MB)
    • 1.1 Pandas Intro and Installation.ipynb (2.0 KB)
    • 2. Series.mp4 (18.0 MB)
    • 2.1 Pandas Series.ipynb (1.5 KB)
    • 3. DataFrame.mp4 (26.5 MB)
    • 3.1 Pandas DataFrame Practical.ipynb (3.2 KB)
    • 4. Read_CSV.mp4 (18.7 MB)
    • 4.1 airport.csv (47.2 KB)
    • 4.2 Read CSV.ipynb (17.3 KB)
    • 5. Analyze Pandas DataFrames.mp4 (48.4 MB)
    • 5.1 airport.csv (47.2 KB)
    • 5.2 Analyzing DataFrames.ipynb (60.1 KB)
    5. Data Visualization
    • 1. Introduction to Matplotlib.mp4 (29.5 MB)
    • 1.1 Matplotlib Intro and Getting started.ipynb (15.1 KB)
    • 2. Type of Plots in Matplotlib.mp4 (47.2 MB)
    • 2.1 Different types of plots in Matplotlib.ipynb (29.3 KB)
    • 3. Seaborn.mp4 (63.9 MB)
    • 3.1 Seaborn.ipynb (67.7 KB)
    6. Data Preprocessing
    • 1. Handling Missing Values.mp4 (64.5 MB)
    • 1.1 Handling Missing Values (1).pptx (620.9 KB)
    • 1.2 Missing Values.ipynb (14.9 KB)
    • 1.3 Placement_Data_Full_Class.csv (19.3 KB)
    • 2. Feature Encoding.mp4 (67.7 MB)
    • 2.1 airport.csv (47.2 KB)
    • 2.2 Feature Encoding.ipynb (36.8 KB)
    • 2.3 Feature Encoding.pptx (492.3 KB)
    • 2.4 Iris.csv (5.0 KB)
    • 3. Feature Scaling.mp4 (56.9 MB)
    • 3.1 Feature Scaling.ipynb (117.3 KB)
    7. Machine Learning
    • 1. Introduction to Machine Learning.mp4 (36.7 MB)
    • 1.1 Machine Learning Introduction.pptx (506.7 KB)
    • 10. Decision Tree.mp4 (73.8 MB)
    • 10.1 Decision Tree Algorithm.pptx (463.4 KB)
    • 10.2 Decision Tree Practical.ipynb (6.4 KB)
    • 10.3 User_Data.csv (10.7 KB)
    • 11. Random Forest.mp4 (48.4 MB)
    • 11.1 Random Forest Algorithm.pptx (400.8 KB)
    • 11.2 Random Forest Practical.ipynb (6.7 KB)
    • 11.3 User_Data.csv (10.7 KB)
    • 12. K Means Clustering.mp4 (66.0 MB)
    • 12.1 K Means Practical.ipynb (60.7 KB)
    • 12.2 K-Means Clustering Algorithm.pptx (588.5 KB)
    • 12.3 Mall_Customers.csv (4.7 KB)
    • 13. Grid Search CV.mp4 (74.0 MB)
    • 13.1 GridSearch CV.ipynb (5.6 KB)
    • 13.2 GridSearchCV.pptx (487.2 KB)
    • 14. Machine Learning Pipeline.mp4 (56.8 MB)
    • 14.1 Machine learning Pipeline.pptx (415.5 KB)
    • 14.2 ML Pipeline.ipynb (10.5 KB)
    • 2. Supervised Machine Learning.mp4 (27.4 MB)
    • 2.1 Supervised Machine Learning.pptx (364.9 KB)
    • 3. Unsupervised Machine Learning.mp4 (22.5 MB)
    • 4. Train Test Split.mp4 (14.6 MB)
    • 5. Regression Analysis.mp4 (55.4 MB)
    • 5.1 Regression Analysis.pptx (541.0 KB)
    • 6. Linear Regression.mp4 (52.2 MB)
    • 6.1 Linear Regression.ipynb (22.0 KB)
    • 6.2 Linear Regression.pptx (360.1 KB)
    • 6.3 Salary_Data.csv (0.4 KB)
    • 7. Logistic Regression.mp4 (74.7 MB)
    • 7.1 Logistic Regression Practical.ipynb (25.3 KB)
    • 7.2 Logistic Regression.pptx (405.2 KB)
    • 7.3 User_Data.csv (10.7 KB)
    • 8. KNN.mp4 (79.0 MB)
    • 8.1 K Nearest Neighbors(KNN).pptx (519.8 KB)
    • 8.2 KNN Practical.ipynb (60.8 KB)
    • 8.3 User_Data.csv (10.7 KB)
    • 9. SVM.mp4 (63.8 MB)
    • 9.1 Support Vector Machine (SVM).pptx (554.8 KB)
    • 9.2 SVM Practical.ipynb (8.7 KB)
    • 9.3 User_Data.csv (10.7 KB)
    8. Projects
    • 1. Car Price Prediction.mp4 (142.9 MB)
    • 1.1 car data.csv (16.8 KB)
    • 1.2 Car Price Prediction.ipynb (41.9 KB)
    • 1.3 Car Price Prediction.pptx (456.2 KB)
    • 2. Customer Segmentation.mp4 (119.9 MB)
    • 2.1 Customer Segmentation using K-means Clustering.pptx (521.4 KB)
    • 2.2 Customer Segmentation.ipynb (60.3 KB)
    • 2.3 Mall_Customers.csv (3.9 KB)
    • 3. Wine Quality Prediction.mp4 (95.5 MB)
    • 3.1 Wine Quality Prediction.ipynb (90.3 KB)
    • 3.2 Wine Quality Prediction.pptx (480.5 KB)
    • 3.3 winequality-red.csv (98.6 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Master Python using ChatGPT



https://DevCourseWeb.com

Published 5/2023
Created by Raj Chhabria
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 43 Lectures ( 5h 39m ) | Size: 2 GB

Become a Python Pro by leveraging the power of ChatGPT.

What you'll learn
Fundamentals of Python Programming Language.
Introduction and multiple use cases of ChatGPT.
Learn how to use ChatGPT for faster development of your coding Projects.
Learn about new technologies like Data Science and Machine Learning with Practical Projects.

Requirements
A desire to learn about latest technologies like ChatGPT, Python, Data Science and Machine Learning.



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Udemy - Master Python using ChatGPT

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Download torrent
2 GB
seeders:22
leechers:13
Udemy - Master Python using ChatGPT

Torrent hash: 8C3C6CDFEE62C0EE01B916F6AD0335D01FABC010