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Master Python using ChatGPT
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[TutsNode.net] - Master Python using ChatGPT (Size: 2.00 GB) (Files: 156)
[TutsNode.net] - Master Python using ChatGPT
8. Projects
1. Car Price Prediction.mp4
2. Customer Segmentation.mp4
3.1 Wine Quality Prediction.ipynb
3. Wine Quality Prediction.mp4
3.3 winequality-red.csv
3.2 Wine Quality Prediction.pptx
2.2 Customer Segmentation.ipynb
1.2 Car Price Prediction.ipynb
1.1 car data.csv
1.3 Car Price Prediction.pptx
2.3 Mall_Customers.csv
2.1 Customer Segmentation using K-means Clustering.pptx
7. Machine Learning
8.2 KNN Practical.ipynb
11.2 Random Forest Practical.ipynb
6.3 Salary_Data.csv
10.2 Decision Tree Practical.ipynb
8. KNN.mp4
13.2 GridSearchCV.pptx
7. Logistic Regression.mp4
7.3 User_Data.csv
13. Grid Search CV.mp4
10. Decision Tree.mp4
12.1 K Means Practical.ipynb
8.3 User_Data.csv
7.1 Logistic Regression Practical.ipynb
6.1 Linear Regression.ipynb
13.1 GridSearch CV.ipynb
12. K Means Clustering.mp4
10.1 Decision Tree Algorithm.pptx
9.3 User_Data.csv
10.3 User_Data.csv
11.3 User_Data.csv
14.2 ML Pipeline.ipynb
9.2 SVM Practical.ipynb
12.3 Mall_Customers.csv
9. SVM.mp4
14. Machine Learning Pipeline.mp4
5. Regression Analysis.mp4
6. Linear Regression.mp4
14.1 Machine learning Pipeline.pptx
11. Random Forest.mp4
1. Introduction to Machine Learning.mp4
1.1 Machine Learning Introduction.pptx
2. Supervised Machine Learning.mp4
7.2 Logistic Regression.pptx
3. Unsupervised Machine Learning.mp4
11.1 Random Forest Algorithm.pptx
4. Train Test Split.mp4
2.1 Supervised Machine Learning.pptx
12.2 K-Means Clustering Algorithm.pptx
6.2 Linear Regression.pptx
9.1 Support Vector Machine (SVM).pptx
5.1 Regression Analysis.pptx
8.1 K Nearest Neighbors(KNN).pptx
3. Numpy
5.1 Array Iterating Practical.ipynb
1.1 Numpy Introduction and Installation.ipynb
2.1 Creating Arrays Numpy.ipynb
6.1 Array Slicing.ipynb
4.1 Array Indexing.ipynb
7.1 Searching and Sorting numpy array prac.ipynb
2. Create a Numpy Array.mp4
3. Shape and Reshape.mp4
6. Slicing.mp4
1. Introduction and Installation.mp4
4. Indexing.mp4
7. Searching and Sorting.mp4
5. Iterating.mp4
5. Data Visualization
2.1 Different types of plots in Matplotlib.ipynb
3.1 Seaborn.ipynb
1.1 Matplotlib Intro and Getting started.ipynb
3. Seaborn.mp4
2. Type of Plots in Matplotlib.mp4
1. Introduction to Matplotlib.mp4
4. Pandas
1.1 Pandas Intro and Installation.ipynb
2.1 Pandas Series.ipynb
5.2 Analyzing DataFrames.ipynb
3.1 Pandas DataFrame Practical.ipynb
5.1 airport.csv
4.1 airport.csv
4.2 Read CSV.ipynb
5. Analyze Pandas DataFrames.mp4
3. DataFrame.mp4
1. Pandas Introduction and Installation.mp4
4. Read_CSV.mp4
2. Series.mp4
6. Data Preprocessing
3.1 Feature Scaling.ipynb
2.1 airport.csv
2. Feature Encoding.mp4
2.2 Feature Encoding.ipynb
1.3 Placement_Data_Full_Class.csv
1.2 Missing Values.ipynb
2.4 Iris.csv
1. Handling Missing Values.mp4
3. Feature Scaling.mp4
1.1 Handling Missing Values (1).pptx
2.3 Feature Encoding.pptx
2. Python
1. Data Types and Variables.mp4
3. Lists.mp4
5. Loops.mp4
4. Conditional Statements.mp4
2. User Input.mp4
1. Introduction
2. ChatGPT Introduction.mp4
1.1 Introduction and key learning outcomes.pptx
3. ChatGPT Practical.mp4
1. Course Introduction and Key Learning Outcomes.mp4
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