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Machine Learning Master Class – Learn Easier than you Think?

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Hai, It’s me Sanjay Machine Learning Master Class Instructor, writing this Blog for you to deliver the values on Machine Learning.

Introduction to A.I & Machine Learning

This Mind map will answer your question

  • What is Machine Learning (M.L)?
  • What are the Types of ML?
  • List of M.L Algorithm?
  • What are the things you need to learn to become a Data scientist?
  • Why do you need to Learn M.L?

Supervised Learning – Classification & Regression

This Mind Map will give precise information about Supervised Learning algorithms


Task – 1: Evaluating Machine Learning Algorithm using custom Dataset

As per the Session, you need to evaluate ML Model for Custom Dataset. You can use any dataset (numerical data in csv format) for the code attached below. TASK is to, You Need to Post the Screen Shot of the Validated Report with your Dataset Tile or Project Title in the Comment Box.

Note: 1. You can download dataset from Kaggle or You can create your own dataset for certain application
2. Don’t use Energy Meter Dataset Provided by us for TASK


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What You Will Learn

Benefits of Internship


A.I Podcast – If 5Minute/ PerDay then A.I ?

You can Listen to the A.I Podcast to Learn A.I Terminology in Maximum 5 Minute / Day


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?Pls Post your Comments?

This Post Has 18 Comments

  1. Deva Uma Devi

    Really very much interested topics you are covering, but while listening audio is resounding and not clear.
    The way of introducing the concepts and summary in terms of mindmaps are excellent

  2. ROHAN

    LR : 94.48076923076924% mean , (2.906957635672559%) std
    CART : 92.23717948717947% mean , (5.290885225501307%) std
    KNN : 92.21794871794872% mean , (3.4258847602528215%) std
    NB : 93.97435897435898% mean , (3.3839840125954543%) std
    SVM : 62.82051282051283% mean , (0.6410256410256432%) std
    LDA : 94.9871794871795% mean , (2.958289926619907%) std

  3. Pradnya

    LR: 94.844961% mean, (3.586181)% std
    LDA: 95.775194% mean, (3.095733)% std
    KNN: 91.572536% mean, (4.917043)% std
    CART: 95.310078% mean, (2.086987)% std
    NB: 93.909192% mean, (3.623226)% std
    SVM: 92.253599% mean, (4.443324)% std

    In SVM model, I have used the gamma parameter ‘scale’ instead of ‘auto’ , because by using ‘auto’ , the accuracy was too less.

  4. Pradnya

    I’m very thankful to you Sanjay Sir. You are doing a great job. Your teaching style is so frankly. And due to this, now I got confidence in python programming as well as Machine Learning. Thank you so much!!

  5. SHIRISHA BOJU

    for yesterday’s assignment using breast cancer data finding machine learning algorithms outputs for the given data is:
    LR: 0.981285 (0.025173)
    LDA: 0.957863 (0.020150)
    KNN: 0.964839 (0.018995)
    NB: 0.941417 (0.027918)
    CART: 0.915615 (0.045433)
    SVM: 0.979014 (0.021946)

  6. John William

    LR: 0.975942 (0.018042)
    LDA: 0.953816 (0.020818)
    KNN: 0.962754 (0.027579)
    CART: 0.951739 (0.033565)
    NB: 0.932029 (0.031328)
    SVM: 0.969324 (0.029562)

  7. Dhanshree

    LR: 0.950831 (0.036608)
    LDR: 0.957863 (0.020150)
    DTC: 0.927187 (0.032254)
    KNN: 0.927187 (0.046122)
    GNB: 0.939037 (0.033207)
    SVM: 0.901495 (0.032657)

  8. Shankar

    Accuracy of LR , standard Deviation of LR
    0.94845 0.03586
    Accuracy of LDA , standard Deviation of LDA
    0.95775 0.03096
    Accuracy of DT , standard Deviation of DT
    0.95089 0.02186
    Accuracy of KNN , standard Deviation of KNN
    0.91573 0.04917
    Accuracy of GNB , standard Deviation of GNB
    0.93909 0.03623
    Accuracy of RFC , standard Deviation of RFC
    0.95548 0.02198
    Accuracy of SVM , standard Deviation of SVM
    0.92254 0.04443

    This is so great I think many people will benefit learning from you. sanjay and jeevarajan sir are very interactive. I hope you reach your stipulated goals sooner and Thank you very much for your intense work.

  9. Shankar

    Accuracy of LR , standard Deviation of LR
    0.94845 0.03586
    Accuracy of LDA , standard Deviation of LDA
    0.95775 0.03096
    Accuracy of DT , standard Deviation of DT
    0.95089 0.02186
    Accuracy of KNN , standard Deviation of KNN
    0.91573 0.04917
    Accuracy of GNB , standard Deviation of GNB
    0.93909 0.03623
    Accuracy of RFC , standard Deviation of RFC
    0.95548 0.02198
    Accuracy of SVM , standard Deviation of SVM
    0.92254 0.04443

    Thank you so much for your intense work, your sessions are really awesome. sanjay and jeevarajan sir are very interactive.

  10. Aatir Nadim

    LR: 0.947343 (0.032476)
    LDA: 0.956087 (0.013680)
    KNN: 0.927488 (0.038094)
    CART: 0.927488 (0.024244)
    NB: 0.940773 (0.029156)
    SVM: 0.637440 (0.007005)

  11. Aatir Nadim

    mean and std

  12. Minal Gavhane

    LR: 0.947285 (0.027702)
    LDA: 0.953130 (0.029324)
    KNN: 0.927677 (0.021649)
    CART: 0.915950 (0.043777)
    NB: 0.931523 (0.033237)
    SVM: 0.626961 (0.004410)

  13. Shubham

    LR : 94.48076923076924% mean , (2.906957635672559%) std
    CART : 92.23717948717947% mean , (5.290885225501307%) std
    KNN : 92.21794871794872% mean , (3.4258847602528215%) std
    NB : 93.97435897435898% mean , (3.3839840125954543%) std
    SVM : 62.82051282051283% mean , (0.6410256410256432%) std
    LDA : 94.9871794871795% mean , (2.958289926619907%) std

  14. Adikaram

    LR: 0.953816 (0.020818)
    LDA: 0.953816 (0.020818)
    KNN: 0.953816 (0.020818)
    CART: 0.953816 (0.020818)
    NB: 0.953816 (0.020818)
    SVM: 0.953816 (0.020818)

  15. KRISHNA VAMSI

    Always great to interact with these techie legends. Education and sharing knowledge! that’s what makes us humans. Doing great job to encourage upcoming generations. I can imagine a smile if a person gains some knowledge through your concepts. God bless and be happy and wealthy.

  16. Rajeev

    LR: 0.955592 (0.030253)
    LDA: 0.953212 (0.034535)
    KNN: 0.929734 (0.040287)
    CART: 0.910853 (0.031071)
    NB: 0.932115 (0.035155)
    SVM: 0.610410 (0.007053)

  17. Rohit Pokhriyal

    LR: 0.985000 (0.018371)
    LDA: 0.952310 (0.019946)
    KNN: 0.952278 (0.009290)
    CART: 0.917089 (0.006093)
    NB: 0.942278 (0.023063)
    SVM: 0.974968 (0.022343)
    Thank you Sanjay!

  18. mahesh

    LD: 0.986047 (0.023716)
    KNN: 0.964839 (0.021656)
    CART: 0.932060 (0.031854)
    NB: 0.943798 (0.031560)
    SVM: 0.979014 (0.021946)
    LDA: 0.953101 (0.017949)
    i tried it sanjay , thanks for teaching us

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