Machine Learning Full Course with Scikit‑Learn | Math + Python + AI | Sagar Chouksey

38 thoughts on “Machine Learning Full Course with Scikit‑Learn | Math + Python + AI | Sagar Chouksey”

1. ❤ Thank you for diving deep into this journey with us – from math to machine learning mastery.

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2. Mean- 73.5
   Median- 73
   Mode- 70

3. df.replace({True: 1, False: 0}, inplace=True)

4. Random forest , XG boost, EDA, feature engineering???

5. 5:29 → Maths Required for Machine Learning
   44:04 → Foundation of Machine Learning (Al vs ML vs DL, Concepts)
   1:05:41 → Core Machine Learning Topics (X/y, Models, Predictions)
   1:14:57 → Data Preprocessing (Missing Data, Encoding, Scaling, Splitting)
   2:05:11 → Supervised Machine Learning (Regression, Classification, KNN, Decision Trees)
   2:59:19 → Model Evaluation & Metrics (Accuracy, Precision, Recall, F1, MAE, MSE, RMSE)
   3:34:00 → Student Score Prediction Project

6. Thank you so much sagar bhaiya for making the concepts so easy to understand. Successsfully completed part1 on 4 september. Keep posting useful content.

7. q2 = score = 50,70,70,90,45,76,99,88
   Mean
   Add = 50+70+70+90+45+76+99+88 = 588
   Count = 8
   Mean = 588/8 = 73.5

   Median = 73.5

   Mode = 70,70

   Sir pahli baar kiya hai reply jarur dijiye

8. Mode:70 , median 67.5 , 294 mean at 16:54

9. I stopped at 2:28:00

10. 😊😅😂❤ DEIXA AI AS ESTRATÉGIAS, MACETES, DICAS, INSTRUÇÕES, TÉCNICAS 😊😅😂❤ HA AQUELES QUE QUEREM SE TORNAR UM ÓTIMO PROFISSIONAL DO RAMO DA PROGRAMAÇÃO 😊😅😂❤

11. at 2:34:20 yaha pe do logo me se teen logo ne is funny!!! 3 me se 2 nahi sir?? Hahahahaaa

12. Bhaiya isme dataset nhi hai

13. excellent 👌👍💯🆗😃

14. Part 2 bhi aayega ?

15. Notes kee link open nahi hoo Rahi hai ???

16. Your lecture is very amazing….
    Please also provide your notes 📖

17. Good

18. Starting ML course 14 sep 2026 10:56 pm

19. Thanks for this course bhai 👍

20. starting on 17/9/26 1pm i'll keep yall updated!!(and like or comment to give me a reminder)

21. 2:18:00

22. Assignment, Q2:
    Mean- 73.25
    Median- 73
    Mode- 70

23. Assignment1
    Mean=73.5
    Median=73
    Mode=70

24. assignment 1 , mode = 74.75 , median = 74.5 mode = 70

25. 16:55 Assignment 1 answer
    mean=73.5
    median=73
    mode=70

26. (90 + 45) ÷ 2
    = 135 ÷ 2
    = 67.5

27. Mean — around 82
    Medium– 90,45
    Mode — 70

28. Es ka 2nd part upload hai kia please bta dy

29. Add = 588
    Median = 511
    Mode = 70

30. Timestamps:
    
    5:29 – 44:04 → Maths Required for Machine Learning
    
    44:04 – 1:05:41 → Foundation of Machine Learning (AI vs ML vs DL, Concepts)
    
    1:05:41 – 1:14:57 → Core Machine Learning Topics (X/y, Models, Predictions)
    
    1:14:57 – 2:05:11 → Data Preprocessing (Missing Data, Encoding, Scaling, Splitting)
    
    2:05:11 – 2:59:19 → Supervised Machine Learning (Regression, Classification, KNN, Decision Trees)
    
    2:59:19 – 3:34:00 → Model Evaluation & Metrics (Accuracy, Precision, Recall, F1, MAE, MSE, RMSE)
    
    3:34:00 – 4:13:19 → Student Score Prediction Project (Start-to-Finish Walkthrough)

31. 2:05:05
    from sklearn.preprocessing import LabelEncoder
    from sklearn.model_selection import train_test_split
    import pandas as pd

    df = pd.read_csv("sample_data.csv")

    df_Label = df.copy()
    le = LabelEncoder()

    print(df.head())

    df_Label['Gender']= le.fit_transform(df_Label['Gender'])
    df_Label['Passed']= le.fit_transform(df_Label['Passed'])

    print(df_Label.head())

    df_Label_encod = pd.get_dummies(df_Label, columns=['City'], dtype= int)

    # X = Features
    X = df_Label_encod.drop(columns=['Name','Passed'])
    print(X.head())

    # y = Label
    y = df_Label_encod[['Passed']]
    print(y.head())

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

    print('X Train Data')
    print(X_train.head())

    print('nX Test Data')
    print(X_test.head())

    print('ny Train Data')
    print(y_train.head())

    print('ny Test Data')
    print(y_test.head())

32. mae and mse both are same that is why they give same answer.

33. Nice video

34. assignment-1
    mean =73.5
    median = 73
    mode =70

35. Teaching method Indian traditional.. No matter you writing with mac pen or pointer..

36. Slowly and gradually software roles demand decreasing day by day. So which developer will sustain till the end?

37. assignment -2 homework

    standard scaler output:
    
    Hourlystudy MarkScored
    
    0 -1.46385 -1.46385
    
    1 -0.87831 -0.87831
    
    2 -0.29277 -0.29277
    
    3 0.29277 0.29277
    
    4 0.87831 0.87831
    
    5 1.46385 1.46385

    output from MinMaxScaler:
    
    Hourlystudy MarkScored
    
    0 0.0 0.0
    
    1 0.2 0.2
    
    2 0.4 0.4
    
    3 0.6 0.6
    
    4 0.8 0.8
    
    5 1.0 1.0
    
    Traning data
    
    Hourlystudy
    
    5 6
    
    2 3
    
    4 5
    
    3 4
    
    testing data
    
    Hourlystudy
    
    0 1
    
    1 2
    
    /n traning_data
    
    MarkScored
    
    5 80
    
    2 50
    
    4 70
    
    3 60
    
    testing_data
    
    MarkScored
    
    0 30
    
    1 40
    
    (base) PS C:UsersstutiDownloadsDATA science coursepractical sk-learn(code with sagar)sk-learn practice code with sagar>

38. 50,70,70,90,45,76,99,88
    
    mean-73.5
    
    median-73
    
    mode-70
    

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