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Advanced Machine Learning in Malayalam

Course Currilcum

      • Introduction to Statistics 00:00:00
      • Jupyter Notebook and Basic Syntax of Python 00:00:00
      • Conditionals and Loops 00:00:00
      • Lists and Tuples 00:00:00
      • Strings in Python 00:00:00
      • Dictionary in Python 00:00:00
      • MINI PROJECT: ROCK-PAPER-SCISSORS GAME 00:00:00
      • Functions in Python Part-1 00:00:00
      • Functions in Python Part-2 00:00:00
      • MINI PROJECT:SUDOKU SOLVER 00:00:00
      • OOPs Intro,Class and Objects 00:00:00
      • Access Modifiers and Inheritance 00:00:00
      • Method overriding,Encapsulation,Polymorphism and imports 00:00:00
      • Files and Exception Handling 00:00:00
      • Chess with GUI part-1 00:00:00
      • Chess with GUI part-2 00:00:00
      • Chess with GUI part-3 00:00:00
      • Chess with GUI part-4 00:00:00
      • File reading in Pandas 00:00:00
      • File writing in Pandas 00:00:00
      • Getting into data manipulation Part-1 00:00:00
      • Getting into data manipulation Part-2 00:00:00
      • Getting into data manipulation Part���3 00:00:00
      • Getting into data manipulation Part-4 00:00:00
      • Advanced data manipulation Part-1 00:00:00
      • Advanced data manipulation Part-2 00:00:00
      • Numpy array manipulation Part-1 00:00:00
      • Numpy array manipulation Part-2 00:00:00
      • Numpy array manipulation Part-3 00:00:00
      • Numpy array manipulation Part-4 00:00:00
      • Data Visualization with pandas Part-1 00:00:00
      • Data Visualization with pandas Part-2 00:00:00
      • Plotly and Cufflinks part-1 00:00:00
      • Plotly and Cufflinks part-2 00:00:00
      • Visualization with Seaborn Part-1 00:00:00
      • Visualization with Seaborn Part-2 00:00:00
      • MySQL 00:00:00
      • SQLite 00:00:00
      • MongoDB 00:00:00
      • API AND EXECUTION FLOW 00:00:00
      • UNDERSTANDING API BY CREATING CALCULATOR 00:00:00
        • Virat Kohli ODI Career Analysis 00:00:00
        • Virat Kohli Test Career Analysis 00:00:00
        • CRISTIANO RONALDO GOALS DATA 00:00:00
        • FIFA DATA EXPLORATION 00:00:00
        • When Would Virat Ovetake Sachin in ODI 00:00:00
        • MESSI VS RONALDO LEAGUE PERFORMANCE 00:00:00
        • MoneyHeist Data Exploration 00:00:00
        • Breaking Bad EDA and a Glimpse of NLP 00:00:00
        • Disney Movies 00:00:00
        • IMDB 1000 MOVIES 00:00:00
        • Netflix Shows 00:00:00
        • Finance Courses in Udemy 00:00:00
        • IBM PAYMENT HISTORY 00:00:00
        • State aggregate expenditure and personal finance data 00:00:00
        • Loan Approval Data 00:00:00
        • Introduction to Statistics 00:00:00
        • Population and Sampling Techniques 00:00:00
        • Variables and Measurements 00:00:00
        • Measures of Central Tendency and Dispersion 00:00:00
        • 5 Number Summary 00:00:00
        • Gaussian(Normal) Distribution and Z score 00:00:00
        • Log-Normal,Bernauli,Binomial and More Distributions 00:00:00
        • Standardization and Normalization 00:00:00
        • Probability 00:00:00
        • Permutations and Combinations 00:00:00
        • Hypothesis Testing 00:00:00
        • Z-test,t-test and Chi-Square test 00:00:00
        • Covariance ,Pearson���s Correlation and Spearman���s Correlation 00:00:00
        • Introduction to Machine Learning 00:00:00
        • PROJECT_INTRO 00:00:00
        • Sampling and Data Exploration 00:00:00
        • Data Preperation and Pipeline Setting 00:00:00
        • Model Building ,Evaluation and Presentation 00:00:00
        • Linear Regression 00:00:00
        • R square and Adjusted R Square 00:00:00
        • Linear Regression and R2_Score Practical 00:00:00
        • Ridge and Lasso Regression 00:00:00
        • Ridge and Lasso Regresson Practicals 00:00:00
        • Logistic Regression 00:00:00
        • Confusion Matrix,Precision,Recall and F-Score 00:00:00
        • Logistic Regression,Confusion Matrix practicals 00:00:00
        • Naive Bayes Indepth Intuition 00:00:00
        • ROC AND AUC 00:00:00
        • Naive Bayes ,ROC and AUC Practicals 00:00:00
        • K Means Clustering with Practical 00:00:00
        • 1. Salary Prediction(Using Flask and Django) 00:00:00
        • Using Flask Framework 00:00:00
        • Using Django Framework 00:00:00
        • 2. Admission Prediction 00:00:00
        • 3.Drug Classification 00:00:00
        • 4.Diabetes Prediction 00:00:00
        • 9.Bank Note Authenticity Prediction 00:00:00
        • Netflix_Shows 00:00:00
        • Breast Cancer 00:00:00
        • EDA_TOOLS_AND_LIBRARIES 00:00:00
        • UBER_EATS 00:00:00
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