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MMK TECHNOLOGIES

MMK TECHNOLOGIES

https://www.mmktech.io

  • B32, F1, C-COLONY, MUTHU SUNDARI APARTMENTS, WATER TANK SOUTH STREET, PERUMALPURAM

    Tirunelveli - 627007

  • +91 9840922213

    Mon-Fri 10:00am-7:30pm

  • km301252@gmail.com

    24 X 7 online support
  • Home
  • Predictive Analytics
    • Back to Basics
    • Learn EDA
    • Correlation
    • Estimates(point & interval)
    • Least Square Method
    • Regression – Basics
    • Regressions
      • Simple Linear Regression
        • Using Excel
        • Using PSPP
        • Using R
        • Using Python-scipy.stats
        • Using statsmodels.api
        • Using Scikit-learn
      • Multiple Linear Regression
        • MLR Problem
        • Using Excel
        • Using Real Statistic Package
        • Using Python
      • Logistic Regression
        • LR Problems
  • Decision Trees
    • CHAID
    • Python-DecisionTreeClassifier
    • Py-DecisionTreeRegressor-1
    • Py-DecisionTreeRegressor-2
  • Pre-Processing
    • Handling of Missing Values
    • Categorical Encoding
      • Other Encoders
        • Ordinal Encoder
        • Binary Encoder
        • HashingEncoder
        • FrequencyEncoding
        • LeaveOneOut Encoder
      • ContrastEncoders
        • PolynomialEncoder
    • Feature Scaling
      • Distribution based
        • Z-score Normalization
        • Robust Scaling
        • Quantile Transformation
      • Range based
      • Scaling to Shape
        • Skewness Calculation
        • Transformations
      • Parametric Scaling
      • Vector Normalizations
        • L1 Normalization – MLR
        • L1 Normalization + Logistic Regression
        • L2 Normalization
      • Other Scaling
        • Decimal Scaling
        • Winzorisation Scaling
  • Feature Selection
    • Filter Method
      • 1.Variance
      • 2. Correlation based
      • 3 Anova (f Test)
      • 4.Chi-Square
      • 5.Univariate Selection
      • 6.Mutual Information
    • Embedded Method
      • 1. Decision Tree/RFC
      • 2. Lasso(L1 Regularization)
      • 3. Ridge (L2 Regularization)
      • 4.Exhaustive Search
    • Wrapper Method
      • 1.Forward Selection
      • 2. Backward Elimination
      • 3.Recursive Elimination
    • Hybrid Selection
    • Deep Learning
      • tanH (Hyperbolic Tangent Activation)
  • Model Evaluation
    • LazyRegressor
  • About
  • Courses
  • e-Book
    • Agile
      • Agile Methodologies
    • Banking
      • Deposits & Loans
      • Financial Calculations
      • Credit Risk Management
    • Mathematics
      • School Mathematics
      • Speed Maths
      • Qualitative Ability
    • CA Courses
      • CA-Foundation Course -Paper 3
  • Contact
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