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Machine Learning Mastery - From Data to Advanced Classifiers --> [ DevCourseWeb ]

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English

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2.53 GB

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55903bafd09e3875d0d16c177067ce62ba9a955b

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29-02-2024 15:49

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File	Size
Get Bonus Downloads Here.url	182.00 B
~Get Your Files Here !/1. Introduction/1. Introduction.mp4	28.07 MB
~Get Your Files Here !/1. Introduction/2. Installing Jupyter.mp4	36.77 MB
~Get Your Files Here !/1. Introduction/3. How to download Python files.mp4	33.32 MB
~Get Your Files Here !/2. Course Contents/1. Import Data.mp4	105.02 MB
~Get Your Files Here !/2. Course Contents/1.1 File 1.ipynb	11.58 kB
~Get Your Files Here !/2. Course Contents/10. 10 displaying the distribution of the data using a box plot.mp4	95.54 MB
~Get Your Files Here !/2. Course Contents/10.1 File 10.ipynb	431.96 kB
~Get Your Files Here !/2. Course Contents/11. 11 displaying the distribution of the data by the different categories.mp4	133.86 MB
~Get Your Files Here !/2. Course Contents/11.1 File 11.ipynb	535.08 kB
~Get Your Files Here !/2. Course Contents/12. 12 visualize the relationship between two variables with jointplot.mp4	135.15 MB
~Get Your Files Here !/2. Course Contents/12.1 File 12.ipynb	955.76 kB
~Get Your Files Here !/2. Course Contents/13. 13 calculating the correlation matrix of the DataFrame.mp4	84.93 MB
~Get Your Files Here !/2. Course Contents/13.1 File 13.ipynb	969.44 kB
~Get Your Files Here !/2. Course Contents/14. 14 creating a mask using NumPy.mp4	57.18 MB
~Get Your Files Here !/2. Course Contents/14.1 File 14.ipynb	972.22 kB
~Get Your Files Here !/2. Course Contents/15. 15 creating a color map using seaborn.mp4	33.63 MB
~Get Your Files Here !/2. Course Contents/15.1 File 15.ipynb	978.05 kB
~Get Your Files Here !/2. Course Contents/16. 16 creating a heatmap using seaborn.mp4	88.84 MB
~Get Your Files Here !/2. Course Contents/16.1 File 16.ipynb	1.02 MB
~Get Your Files Here !/2. Course Contents/17. 17 calculating the number of outliers.mp4	218.25 MB
~Get Your Files Here !/2. Course Contents/17.1 File 17.ipynb	1.05 MB
~Get Your Files Here !/2. Course Contents/18. 18 standardizing features.mp4	58.84 MB
~Get Your Files Here !/2. Course Contents/18.1 File 18.ipynb	71.84 kB
~Get Your Files Here !/2. Course Contents/19. 19 Hypothesis testing.mp4	34.92 MB
~Get Your Files Here !/2. Course Contents/19.1 File 19.ipynb	75.54 kB
~Get Your Files Here !/2. Course Contents/2. 2 visualizing missing data in a dataset.mp4	34.28 MB
~Get Your Files Here !/2. Course Contents/2.1 File 2.ipynb	90.77 kB
~Get Your Files Here !/2. Course Contents/20. 20 Normalization.mp4	131.91 MB
~Get Your Files Here !/2. Course Contents/20.1 File 20.ipynb	112.41 kB
~Get Your Files Here !/2. Course Contents/21. 21 split the data into training and testing sets.mp4	147.05 MB
~Get Your Files Here !/2. Course Contents/21.1 File 21.ipynb	141.83 kB
~Get Your Files Here !/2. Course Contents/22. 22 Start traning SVC and Learn Hyperparameters.mp4	62.61 MB
~Get Your Files Here !/2. Course Contents/22.1 File 22.ipynb	144.52 kB
~Get Your Files Here !/2. Course Contents/23. 23 find the best hyperparameter.mp4	100.41 MB
~Get Your Files Here !/2. Course Contents/23.1 File 23.ipynb	147.56 kB
~Get Your Files Here !/2. Course Contents/24. 24 make predictions on the test data and avaluate the model.mp4	134.81 MB
~Get Your Files Here !/2. Course Contents/24.1 File 24.ipynb	155.38 kB
~Get Your Files Here !/2. Course Contents/25. 25 Train RandomForestClassifier.mp4	101.82 MB
~Get Your Files Here !/2. Course Contents/25.1 File 25.ipynb	160.21 kB
~Get Your Files Here !/2. Course Contents/26. 26 Train XGBClassifier.mp4	63.70 MB
~Get Your Files Here !/2. Course Contents/26.1 File 26.ipynb	165.72 kB
~Get Your Files Here !/2. Course Contents/27. 27 Train KNeighborsClassifier.mp4	47.88 MB
~Get Your Files Here !/2. Course Contents/27.1 File 27.ipynb	171.20 kB
~Get Your Files Here !/2. Course Contents/28. 28 Train LGBMClassifier.mp4	59.79 MB
~Get Your Files Here !/2. Course Contents/28.1 File 28.ipynb	180.82 kB
~Get Your Files Here !/2. Course Contents/29. 29 calculate the (ROC) curve and the (AUC) score.mp4	104.91 MB
~Get Your Files Here !/2. Course Contents/29.1 File 29.ipynb	237.97 kB
~Get Your Files Here !/2. Course Contents/3. 3 calculating statistical information.mp4	57.89 MB
~Get Your Files Here !/2. Course Contents/3.1 File 3.ipynb	101.61 kB
~Get Your Files Here !/2. Course Contents/4. 4 checking for duplicate rows in the DataFrame.mp4	30.43 MB
~Get Your Files Here !/2. Course Contents/4.1 File 4.ipynb	103.07 kB
~Get Your Files Here !/2. Course Contents/5. 5 calculating the number of distinct values in each column.mp4	56.18 MB
~Get Your Files Here !/2. Course Contents/5.1 File 5.ipynb	105.63 kB
~Get Your Files Here !/2. Course Contents/6. 6 checking for missing or null values in the DataFrame.mp4	34.20 MB
~Get Your Files Here !/2. Course Contents/6.1 File 6.ipynb	117.27 kB
~Get Your Files Here !/2. Course Contents/7. 7 Cleaning the data.mp4	71.18 MB
~Get Your Files Here !/2. Course Contents/7.1 File 7.ipynb	127.95 kB
~Get Your Files Here !/2. Course Contents/8. 8 creating a new column called 'Label' in the DataFrame.mp4	78.66 MB
~Get Your Files Here !/2. Course Contents/8.1 File 8.ipynb	158.26 kB
~Get Your Files Here !/2. Course Contents/9. 9 creating a histogram plot.mp4	117.57 MB
~Get Your Files Here !/Bonus Resources.txt	386.00 B

Description

[ DevCourseWeb.com ] Machine Learning Mastery: From Data to Advanced Classifiers

If You Need More Stuff, kindly Visit and Support Us -->> https://DevCourseWeb.com

Published 2/2024
Created by Abdurrahman TEKIN
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 32 Lectures ( 2h 52m ) | Size: 2.52 GB

Mastering Machine Learning: From Data Import to Model Evaluation with Advanced Classifiers

What you'll learn:
Importing and preparing data for analysis.
Cleaning and preprocessing techniques for data integrity.
Effective data visualization methods.
Understanding and utilizing correlation heatmaps.
Preprocessing steps for feature scaling and handling categorical variables.
Proper data splitting for training and testing.
Implementation of machine learning models: Support Vector Classifier (SVC), RandomForestClassifier, XGBClassifier, KNeighborsClassifier, LGBMClassifier
Evaluation using Receiver Operator Characteristic (ROC) curve.

Requirements:
Basic understanding of programming concepts and Python programming language.
Familiarity with data manipulation using libraries such as Pandas and NumPy.

If You Need More Stuff, kindly Visit and Support Us -->> https://CourseWikia.com

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We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...