Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
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README & documentation
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100 Days of Machine Learning Coding as proposed by Siraj Raval Get the datasets from here Check out the code from here. Check out the code from here. Check out the code from here. Moving forward into #100DaysOfMLCode today I dived into the deeper depth of what Logistic Regression actually is and what is the math involved behind it. Learned how cost function is calculated and then how to apply gradient descent algorithm to cost function to minimize the error in prediction. Due to less time I will now be posting an infographic on alternate days. Also if someone wants to help me out in documentaion of code and already has some experince in the field and knows Markdown for github please contact me on LinkedIn :) . Check out the Code here #100DaysOfMLCode To clear my insights on logistic regression I was searching on the internet for some resource…
Read the full README ↗ · Preview checked 2026-10-31T00:55:05.723Z
Inside the original README — Document outline
- 100-Days-Of-ML-Code
- Data PreProcessing | Day 1
- Simple Linear Regression | Day 2
- Multiple Linear Regression | Day 3
- Logistic Regression | Day 4
- Logistic Regression | Day 5
- Implementing Logistic Regression | Day 6
- K Nearest Neighbours | Day 7
- Math Behind Logistic Regression | Day 8
- Support Vector Machines | Day 9
- SVM and KNN | Day 10
- Implementation of K-NN | Day 11
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What this repository does
100 Days of ML Coding
Repository facts
- Owner
- Avik-Jain
- Primary language
- Not reported
- Stars
- 52,018
- Forks
- 11,634
- Open issues + pull requests
- 68
- License
- MIT
- Archived
- No
- Default branch
- master
- Created
- 2018-07-05T09:11:43.000Z
- Last push
- 2023-12-29T07:57:53.000Z
Topics and intended use
Owner-supplied topics: 100-days-of-code-log, 100daysofcode, deep-learning, implementation, infographics, linear-algebra, linear-regression, logistic-regression, machine-learning, machine-learning-algorithms, naive-bayes-classifier, python, scikit-learn, siraj-raval, siraj-raval-challenge, support-vector-machines, svm, tutorial
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