Master Python using ChatGPT | 22D37731C23B91059C37C5306143E6FE8BEE1AE0

Master Python using ChatGPT

Name	Master Python using ChatGPT	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	2.2 GB
Total Files	156
Last Seen
Hash	22D37731C23B91059C37C5306143E6FE8BEE1AE0

/8. Projects/
1. Car Price Prediction.mp4	149.9 MB

TutsNode.net.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/7. Machine Learning/
8.2 KNN Practical.ipynb	62.3 KB
11.2 Random Forest Practical.ipynb	6.8 KB
6.3 Salary_Data.csv	0.5 KB
10.2 Decision Tree Practical.ipynb	6.5 KB
8. KNN.mp4	82.9 MB
13.2 GridSearchCV.pptx	498.9 KB
7. Logistic Regression.mp4	78.3 MB
7.3 User_Data.csv	10.9 KB
13. Grid Search CV.mp4	77.6 MB
10. Decision Tree.mp4	77.3 MB
12.1 K Means Practical.ipynb	62.2 KB
8.3 User_Data.csv	10.9 KB
7.1 Logistic Regression Practical.ipynb	25.9 KB
6.1 Linear Regression.ipynb	22.6 KB
13.1 GridSearch CV.ipynb	5.7 KB
12. K Means Clustering.mp4	69.2 MB
10.1 Decision Tree Algorithm.pptx	474.5 KB
9.3 User_Data.csv	10.9 KB
10.3 User_Data.csv	10.9 KB
11.3 User_Data.csv	10.9 KB
14.2 ML Pipeline.ipynb	10.8 KB
9.2 SVM Practical.ipynb	8.9 KB
12.3 Mall_Customers.csv	4.8 KB
9. SVM.mp4	66.9 MB
14. Machine Learning Pipeline.mp4	59.6 MB
5. Regression Analysis.mp4	58.1 MB
6. Linear Regression.mp4	54.8 MB
14.1 Machine learning Pipeline.pptx	425.5 KB
11. Random Forest.mp4	50.7 MB
1. Introduction to Machine Learning.mp4	38.5 MB
1.1 Machine Learning Introduction.pptx	518.9 KB
2. Supervised Machine Learning.mp4	28.7 MB
7.2 Logistic Regression.pptx	414.9 KB
3. Unsupervised Machine Learning.mp4	23.6 MB
11.1 Random Forest Algorithm.pptx	410.5 KB
4. Train Test Split.mp4	15.3 MB
2.1 Supervised Machine Learning.pptx	373.6 KB
12.2 K-Means Clustering Algorithm.pptx	602.6 KB
6.2 Linear Regression.pptx	368.8 KB
9.1 Support Vector Machine (SVM).pptx	568.1 KB
5.1 Regression Analysis.pptx	554.0 KB
8.1 K Nearest Neighbors(KNN).pptx	532.3 KB
/3. Numpy/
5.1 Array Iterating Practical.ipynb	2.2 KB
1.1 Numpy Introduction and Installation.ipynb	1.7 KB
2.1 Creating Arrays Numpy.ipynb	4.6 KB
6.1 Array Slicing.ipynb	4.4 KB
4.1 Array Indexing.ipynb	4.1 KB
7.1 Searching and Sorting numpy array prac.ipynb	4.0 KB
2. Create a Numpy Array.mp4	55.6 MB
3. Shape and Reshape.mp4	52.5 MB
6. Slicing.mp4	45.3 MB
1. Introduction and Installation.mp4	37.7 MB
4. Indexing.mp4	37.5 MB
7. Searching and Sorting.mp4	34.2 MB
5. Iterating.mp4	27.0 MB
.pad/
0	0.2 KB
1	0.1 KB
2	0.6 KB
3	1.1 KB
4	1.3 KB
5	0.6 KB
6	0.5 KB
7	2.8 KB
8	1.6 KB
9	0.2 KB
10	40.2 KB
11	237.7 KB
12	111.0 KB
13	191.5 KB
14	70.1 KB
15	7.7 KB
16	277.0 KB
17	24.9 KB
18	81.5 KB
19	154.2 KB
20	337.7 KB
21	356.9 KB
22	285.8 KB
23	339.6 KB
24	69.1 KB
25	38.6 KB
26	203.6 KB
27	364.5 KB
28	4.4 KB
29	242.4 KB
30	107.0 KB
31	77.1 KB
32	135.8 KB
33	23.3 KB
34	214.4 KB
35	72.3 KB
36	306.5 KB
37	300.2 KB
38	33.2 KB
39	37.8 KB
40	55.6 KB
41	8.9 KB
42	237.8 KB
43	412.8 KB
44	77.2 KB
45	480.5 KB
46	494.6 KB
47	514.7 KB
48	516.3 KB
/8. Projects/
2. Customer Segmentation.mp4	125.7 MB
3.1 Wine Quality Prediction.ipynb	92.5 KB
3. Wine Quality Prediction.mp4	100.1 MB
3.3 winequality-red.csv	101.0 KB
3.2 Wine Quality Prediction.pptx	492.0 KB
2.2 Customer Segmentation.ipynb	61.8 KB
1.2 Car Price Prediction.ipynb	42.9 KB
1.1 car data.csv	17.2 KB
1.3 Car Price Prediction.pptx	467.1 KB
2.3 Mall_Customers.csv	4.0 KB
2.1 Customer Segmentation using K-means Clustering.pptx	533.9 KB
/5. Data Visualization/
2.1 Different types of plots in Matplotlib.ipynb	30.0 KB
3.1 Seaborn.ipynb	69.3 KB
1.1 Matplotlib Intro and Getting started.ipynb	15.5 KB
3. Seaborn.mp4	67.0 MB
2. Type of Plots in Matplotlib.mp4	49.5 MB
1. Introduction to Matplotlib.mp4	30.9 MB
/4. Pandas/
1.1 Pandas Intro and Installation.ipynb	2.0 KB
2.1 Pandas Series.ipynb	1.6 KB
5.2 Analyzing DataFrames.ipynb	61.6 KB
3.1 Pandas DataFrame Practical.ipynb	3.3 KB
5.1 airport.csv	48.4 KB
4.1 airport.csv	48.4 KB
4.2 Read CSV.ipynb	17.7 KB
5. Analyze Pandas DataFrames.mp4	50.8 MB
3. DataFrame.mp4	27.8 MB
1. Pandas Introduction and Installation.mp4	27.4 MB
4. Read_CSV.mp4	19.6 MB
2. Series.mp4	18.8 MB
/6. Data Preprocessing/
3.1 Feature Scaling.ipynb	120.1 KB
2.1 airport.csv	48.4 KB
2. Feature Encoding.mp4	71.0 MB
2.2 Feature Encoding.ipynb	37.7 KB
1.3 Placement_Data_Full_Class.csv	19.7 KB
1.2 Missing Values.ipynb	15.3 KB
2.4 Iris.csv	5.1 KB
1. Handling Missing Values.mp4	67.7 MB
3. Feature Scaling.mp4	59.7 MB
1.1 Handling Missing Values (1).pptx	635.8 KB
2.3 Feature Encoding.pptx	504.1 KB
/2. Python/
1. Data Types and Variables.mp4	40.1 MB
3. Lists.mp4	38.2 MB
5. Loops.mp4	29.1 MB
4. Conditional Statements.mp4	20.7 MB
2. User Input.mp4	13.1 MB
/1. Introduction/
2. ChatGPT Introduction.mp4	27.7 MB
1.1 Introduction and key learning outcomes.pptx	381.5 KB
3. ChatGPT Practical.mp4	18.8 MB
1. Course Introduction and Key Learning Outcomes.mp4	9.7 MB
Total files 156