Machine learning using Python | C92CBF3038A410BA658A2135E3D99651F4E88799

Machine learning using Python

Name	Machine learning using Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	3.9 GB
Total Files	142
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Hash	C92CBF3038A410BA658A2135E3D99651F4E88799

/.../5. Module 6 What is Linear Regression/
5. Session 5 - Years vs Salary.mp4	187.1 MB

TutsNode.net.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/8. Module 9/
1. Session1- Images in Matplotlib.srt	45.3 KB
3. Session 3- Digits Classification.srt	32.3 KB
2. Session2 - Solution on Checkerboard.srt	19.8 KB
4. Session 4- What is SVM.srt	18.9 KB
5. Session 5- Coding SVM in Sklearn.srt	17.4 KB
1. Session1- Images in Matplotlib.mp4	168.2 MB
3. Session 3- Digits Classification.mp4	134.6 MB
5. Session 5- Coding SVM in Sklearn.mp4	83.3 MB
2. Session2 - Solution on Checkerboard.mp4	68.7 MB
4. Session 4- What is SVM.mp4	66.4 MB
/.../5. Module 6 What is Linear Regression/
5. Session 5 - Years vs Salary.srt	38.6 KB
7. Session 7 - Joblib.srt	27.6 KB
4. Session 4- Scratch vs Sklearn.srt	26.7 KB
2. Session 2- Coding from scratch.srt	23.1 KB
1. Session 1 - What is Linear Regression.srt	15.3 KB
6. Session 6- Accuracy and Plot.srt	11.4 KB
3. Session 3 - Coding from scratch - Part 2.srt	11.4 KB
2. Session 2- Coding from scratch.mp4	112.4 MB
7. Session 7 - Joblib.mp4	109.6 MB
4. Session 4- Scratch vs Sklearn.mp4	98.8 MB
3. Session 3 - Coding from scratch - Part 2.mp4	71.9 MB
1. Session 1 - What is Linear Regression.mp4	56.6 MB
6. Session 6- Accuracy and Plot.mp4	51.4 MB
/.../1. Module 2 - Data Structures in Python/
1. Functions and Jupyter Installation.srt	36.4 KB
2. Lists in Python.srt	32.9 KB
3. Module 2, Session 3.srt	24.8 KB
1. Functions and Jupyter Installation.mp4	110.3 MB
2. Lists in Python.mp4	108.9 MB
3. Module 2, Session 3.mp4	94.1 MB
/2. Module 3 Numpy/
1. Session 3 - Numpy Part 3.srt	36.4 KB
1. Session 3 - Numpy Part 3.mp4	133.4 MB
/4. Module 5 Pandas/
2. Session 2- DataFrames Part 1.srt	34.6 KB
1. Session1 - Series in Pandas.srt	30.3 KB
9. Session 9 - EDA.srt	29.7 KB
3. Session 3 - DataFrames Part 2.srt	28.7 KB
8. Session 8-Solution.srt	20.8 KB
5. Session 5- CSV File.srt	17.5 KB
6. Session 6- NaN Values.srt	17.2 KB
4. Session 4- Index of DataFrame.srt	5.3 KB
7. Session 7- Exercise.srt	1.7 KB
2. Session 2- DataFrames Part 1.mp4	132.1 MB
9. Session 9 - EDA.mp4	119.4 MB
1. Session1 - Series in Pandas.mp4	108.7 MB
3. Session 3 - DataFrames Part 2.mp4	101.8 MB
8. Session 8-Solution.mp4	90.2 MB
5. Session 5- CSV File.mp4	76.2 MB
6. Session 6- NaN Values.mp4	75.3 MB
4. Session 4- Index of DataFrame.mp4	22.3 MB
7. Session 7- Exercise.mp4	12.1 MB
/3. Module 4/
1. Session 1 - Line Plots.srt	32.9 KB
1. Session 1 - Line Plots.mp4	118.1 MB
/.../6. Module 7 Basic Intuition on Logistic Regression/
5. Salary vs Exp.srt	30.7 KB
3. Session 2 - Logistic Regression from Scratch Part 2.srt	25.0 KB
2. Session 2 - Logistic Regression from Scratch Part 1.srt	21.3 KB
5. Salary vs Exp.mp4	181.9 MB
4. Session 4 - Logistic Regression using Sklearn.srt	14.1 KB
1. Session 1- Basic Intuition on Logistic Regression.srt	10.5 KB
3. Session 2 - Logistic Regression from Scratch Part 2.mp4	78.9 MB
2. Session 2 - Logistic Regression from Scratch Part 1.mp4	72.8 MB
4. Session 4 - Logistic Regression using Sklearn.mp4	63.0 MB
1. Session 1- Basic Intuition on Logistic Regression.mp4	46.6 MB
/.../7. Module 8 KNN algorithm/
2. Session 2- KNN using Sklearn.srt	26.6 KB
1. Session 1 KNN algorithm.srt	22.4 KB
4. Session 4 - Iris Dataset.srt	5.3 KB
5. Session 5- Iris Coding.srt	13.8 KB
7. Session 7- Prediction of values.srt	13.6 KB
3. Session 3 - Datasets Sklearn.srt	11.0 KB
6. Session 6- Visualization.srt	7.7 KB
2. Session 2- KNN using Sklearn.mp4	121.1 MB
1. Session 1 KNN algorithm.mp4	100.5 MB
5. Session 5- Iris Coding.mp4	75.5 MB
3. Session 3 - Datasets Sklearn.mp4	65.4 MB
7. Session 7- Prediction of values.mp4	61.2 MB
4. Session 4 - Iris Dataset.mp4	44.3 MB
6. Session 6- Visualization.mp4	34.3 MB
/9. Module 10/
4. Session 4 - CLustering in Sklearn.srt	22.8 KB
6. Session 6 - Maths behind Elbow Method.srt	21.0 KB
9. Assignment 2 - Clustering Questions Answered.srt	19.6 KB
5. Session 5-Elbow-Method.srt	14.4 KB
3. Session 3-Maths-behind-KMeans.srt	9.7 KB
2. Session 2-Flowchart-of-KMeans.srt	5.3 KB
1. Session 1-What-is-Clustering.srt	3.6 KB
7. Session 7-Market-Segmentation.srt	1.7 KB
8. Assignment 2 - Clustering Questions.srt	0.9 KB
6. Session 6 - Maths behind Elbow Method.mp4	95.3 MB
9. Assignment 2 - Clustering Questions Answered.mp4	88.0 MB
4. Session 4 - CLustering in Sklearn.mp4	79.9 MB
5. Session 5-Elbow-Method.mp4	58.8 MB
3. Session 3-Maths-behind-KMeans.mp4	42.5 MB
2. Session 2-Flowchart-of-KMeans.mp4	16.2 MB
1. Session 1-What-is-Clustering.mp4	16.1 MB
8. Assignment 2 - Clustering Questions.mp4	5.3 MB
7. Session 7-Market-Segmentation.mp4	4.5 MB
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Total files 142