https://github.com/sarincr/machine-learning-python-bootcamp

Basic exercises on Machine Learning with Python , Reference Book : Python for Probability, Statistics, and Machine Learning by José Unpingco
https://github.com/sarincr/machine-learning-python-bootcamp

algorithms artificial-intelligence deep-learning logistic-regression machine-learning machine-learning-algorithms machinelearning machinelearning-python matplotlib neural-network numpy pandas python python3 regression scikit-learn scipy sklearn statistics support-vector-machine

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Basic exercises on Machine Learning with Python , Reference Book : Python for Probability, Statistics, and Machine Learning by José Unpingco

• Host: GitHub
• URL: https://github.com/sarincr/machine-learning-python-bootcamp
• Owner: sarincr
• Created: 2019-07-13T07:22:34.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-03-27T07:11:18.000Z (over 2 years ago)
• Last Synced: 2023-10-19T18:27:11.880Z (about 1 year ago)
• Topics: algorithms, artificial-intelligence, deep-learning, logistic-regression, machine-learning, machine-learning-algorithms, machinelearning, machinelearning-python, matplotlib, neural-network, numpy, pandas, python, python3, regression, scikit-learn, scipy, sklearn, statistics, support-vector-machine
• Language: Jupyter Notebook
• Homepage:
• Size: 20.5 MB
• Stars: 7
• Watchers: 3
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Basic-exercises-on-Machine-Learning-with-Python

Basic exercises on Machine Learning with Python

![alt text](https://github.com/sarincr/Machine-Learning-Python-Bootcamp/blob/master/IBM%20Badges.png)

01.Python Basics \

02.Arrays\

03.Numpy\

04.Lists\

05.InOut\

06.Tuple\

07.Sets\

08.Dictionary\

09.Directory\

10.Exceptions\

11.Custom Exceptions\

12.Class\

13.Inheritance\

14.Modules\

15.Math and Stats\

16.Matplotlib\

17.Seaborn\

18.SimPy\

19.Pendulum\

20.Arow module\

21.Decision TreesVIz\

22.Requests\

23.Tensorflow Basics\

24.Stumpy\

25.Linear_Regression\

26.Logistic_regression\

27.XGBRegressor\

28.Ridge_Regression\

29.Support_Vector_Regression\

30.Lasso_Regression\

31.Bayesian_Ridge_Regression\

32.MLPRegressor\

33.Random_Forest_Regression\

34.PLSRegression\

35.DecisionTreeRegressor\

36.Agglomerative_Clustering\

37.ARIMA\

38.K_Nearest_Neighbors_Regression\

39.SVC_linear\

40.SVC_RBF\

41.SVC_Poly\

42.MLPClassifier\

43.KNeighborsClassifier\

44.GaussianProcessClassifier\

45.DecisionTreeClassifier\

46.RandomForestClassifier\

47.AdaBoostClassifier\

48.GaussianNB\

49.K_Means_Clustering\