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[ DevCourseWeb com ] Udemy - Complete Machine Learning Course for Beginners - in Python
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Get Bonus Downloads Here.url (Size: 2.21 GB) (Files: 103)
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01 - Introduction to machine learning (Theory)
001 Introduction.mp4
001 Introduction_en.vtt
002 Machine learning types.mp4
002 Machine learning types_en.vtt
003 Machine learning workflow.mp4
003 Machine learning workflow_en.vtt
02 - Mathematics in machine learning (Theory)
001 Data an linear algebra.mp4
001 Data an linear algebra_en.vtt
002 Calculus.mp4
002 Calculus_en.vtt
003 Statistics and types of sampeling.html
004 Descriptive and inferential statistics.mp4
004 Descriptive and inferential statistics_en.vtt
005 Probability.mp4
005 Probability_en.vtt
03 - Python (Practice)
001 Intro to setting up Python.mp4
001 Intro to setting up Python_en.vtt
002 Basic coding skills.mp4
002 Basic coding skills_en.vtt
40293650-intro-python-code.py
04 - Machine learning libraries (Practice)
001 NumPy - Python.mp4
001 NumPy - Python_en.vtt
002 Pandas - Python.mp4
002 Pandas - Python_en.vtt
003 Pandas (2) - Python.mp4
003 Pandas (2) - Python_en.vtt
004 Matplotlib - Python.mp4
004 Matplotlib - Python_en.vtt
005 Natural language processing (NLP).mp4
005 Natural language processing (NLP)_en.vtt
006 Scikit - Python.mp4
006 Scikit - Python_en.vtt
40293606-intro-to-numpy.ipynb
40293618-intro-to-panda.ipynb
40293624-intro-to-matplotlib.ipynb
40293630-intro-to-nltk.ipynb
40293644-intro-to-scikitLearn.ipynb
05 - Supervised learning (Practice)
001 Linear regression - Theory.mp4
001 Linear regression - Theory_en.vtt
002 Linear regression - Practice.html
003 Logistic regression - Theory.mp4
003 Logistic regression - Theory_en.vtt
004 Logistic regression - Practice (1).html
005 KNN - Theory.mp4
005 KNN - Theory_en.vtt
006 KNN - Practice.mp4
006 KNN - Practice_en.vtt
007 KNN - Practice (2).mp4
007 KNN - Practice (2)_en.vtt
008 Naive Bayes - Theory.mp4
008 Naive Bayes - Theory_en.vtt
009 Naive Bayes - Practice.mp4
009 Naive Bayes - Practice_en.vtt
010 Naive Bayes - Practice (2).mp4
010 Naive Bayes - Practice (2)_en.vtt
011 Naive Bayes - Practice (3).mp4
011 Naive Bayes - Practice (3)_en.vtt
012 SVM - Theory.mp4
012 SVM - Theory_en.vtt
013 SVM - Practice.mp4
013 SVM - Practice_en.vtt
014 Decision Tree - Theory.mp4
014 Decision Tree - Theory_en.vtt
015 Decision Tree - Practice.mp4
015 Decision Tree - Practice_en.vtt
40293478-logistic-regresssion.ipynb
40293480-diabetes.csv
40293492-knn.ipynb
40293494-iris.csv
40293502-naive-bayes.ipynb
40293506-Social-Network-Ads.csv
40293512-pulsar-stars.csv
40293520-svm.ipynb
40293526-car-evaluation.csv
40293530-dt.ipynb
40293688-linear-regression.ipynb
40293692-fathersonheight.csv
06 - Unsupervised learning (Practice)
001 Kmeans - Theory.mp4
001 Kmeans - Theory_en.vtt
002 Kmeans - Practice.mp4
002 Kmeans - Practice_en.vtt
003 Hierachical Clustering - Theory.mp4
003 Hierachical Clustering - Theory_en.vtt
004 Hierachical Clustering - Practice.mp4
004 Hierachical Clustering - Practice_en.vtt
005 DBScan - Theory.mp4
005 DBScan - Theory_en.vtt
006 DBScan - Practice.html
40293700-k-means.ipynb
40293708-hierarchical-clustering.ipynb
40293710-shopping-data.csv
07 - Project Fake news detection
001 Part 1.mp4
001 Part 1_en.vtt
002 Part 2.mp4
002 Part 2_en.vtt
003 Part 3.mp4
003 Part 3_en.vtt
004 Part 4.mp4
004 Part 4_en.vtt
40293574-fake-news-detection.ipynb
40293580-data.csv
Bonus Resources.txt
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