CHAITANYA BHARATHI INSTITUTE OF TECHNOLOGY (A)
  • Machine Learning Using Python-OE-1-EEE-D1&D2-VII Sem-2020-21
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    MLUP MARKS LINK
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    Syllabus Related Files
    MLUP syllabus
    MLUP Lesson Plan
    ONLINE CLASS RECORDING LINKS
    Class-1: introduction to machine learning (taken on 10/82020)
    Class-2 : introduction to python (taken on 13/8/2020)
    class-3: Basics of Python(taken on 17/8/2020)
    class-4 MLUP(if, if...else, loops)(taken on 18/8/2020)
    Class-5: Strings and functions in Python (taken on 20/8/2020)
    class-6: PYTHON SPECIFIC DATA STRUCTURES(24/8/2020)
    class-7: Data structures in Python(taken on 27/8/2020)
    Class-8: tuples and files(taken on 31/8/2020)
    Class-9: ML process(taken on 1/9/2020)
    Class-10: Data frame (taken on 3/9/2020)
    Class-11: Data visualization(taken on 7/9/2020)
    Class-12: Data visualization(taken on 8/9/2020)
    Class-13: Box plot and feature engineering(taken on 10/9/2020)
    class-14:Handling Numerical values(taken on14/9/2020)
    Class-15: Handling categorical values and Time features(taken on 15/9/2020)
    Class-16: TFIRD and linear regression(taken on 17/9/2020)
    Class-17: linear regression(taken on 21/9/2020)
    Class-18: linear regression(taken on 22/9/2020)
    Class-19: Gradient Descent(taken on 24/9/2020)
    Class-20: Multiple Linear Regression(taken on 29/9/2020)
    Class-21: Polynomial Regression(taken on 1/10/2020)
    Class-22: Model assessment(taken on 6/10/2020)
    Class-23: Regularization(taken on 8/10/2020)
    Class-24: KNN(taken on 9/10/2020)
    Class-25: Revision for mid-1(taken on 10/10/2020)
    Class-26: Kernel Regression(taken on 12/10/2020)
    Class-27: LOGISTIC REGRESSION(taken on 19/10/2020)
    Class-28: LOGISTIC REGRESSION(taken on 20/10/2020)
    Class-29: DECISION TREES(taken on 22/10/2020)
    Class-30: DECISION TREES(taken on 27/10/2020)
    Class-31: Gini index technique(taken on 29/10/2020)
    Class-32: Random Forest and Naïve Bayes classification(taken on 2/11/2020)
    Class-33: Classification algorithm coding(taken on 3/11/2020)
    Class-34: Clustering(taken on 5/11/2020)
    Class-35: Agglomerative Clustering(taken on 9/11/2020)
    Class-36: time series analysis(taken on 10/11/2020)
    Class-37: regular expressions(taken on 12/11/2020)
    Class-38: NLP & window functions(taken on 16/11/2020)
    Class-39: Vectirization & Deep Learning(taken on 17/11/2020)
    Class-40: Neural Network Architecture(taken on 19/11/2020)
    Class-41: Recommendation systems(taken on 23/11/2020)
    Class-42: Rivision for mid-2(taken on 24/11/2020)
    Class-43:Discussion of mid-2 paper(taken on 26/11/2020)
    Unit-1
    Introduction to Python
    Introduction to Machine Learning
    Python specific data structures
    ML PROCESS
    Unit-2
    Data visualization
    Feature Engineering
    DATA FRAME HANDLING
    UNIT-3
    REGRESSION
    Regularization
    LOGISTIC REGRESSION
    Decision Tree - ID3 algorithm
    Decision Tree - GINI index
    Random forest and Naive
    Naive Bayes
    UNIT-4
    K-MEANS CLUSTERING
    agglomerative algorithm
    UNIT-5
    Deep Learning
    Slip Tests
    slip test-3
    CODE
    unit-1 TB code
    unit-2 TB code
    unit-3 TB code
    unit-4 TB code
    unit-5 TB code
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    Machine Learning Using Python-OE-1-EEE-D1&D2-VII Sem-2020-21
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    1. Home
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    3. Electrical and Electronics Engineering
    4. UG
    5. AY 2020-21
    6. VII Semester
    7. Machine Learning Using Python-OE-1-EEE-D1&D2-VII Sem-2020-21
    8. Summary

    Machine Learning Using Python-OE-1-EEE-D1&D2-VII Sem-2020-21

    • Teacher: Smt. E. Swathi Assistant Professor
    Skill Level: Beginner

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