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Samridh Vikhas
- Rate $17
- Response 1h
-
Students12
Number of students Samridh Vikhas has accompanied since arriving at Superprof
Number of students Samridh Vikhas has accompanied since arriving at Superprof

$17/h
1st lesson free
- Machine learning
Machine Learning from the foundations up — for students who want to understand their models, not just run them
- Machine learning
Lesson location
Recommended
Samridh Vikhas is a respected tutor in our community. They are highly recommended for their commitment and the quality of their lessons. An excellent choice to progress with confidence.
About Samridh Vikhas
I'm a data analyst who works with real data every day — building pipelines, cleaning things that arrive broken, and producing analysis that people make decisions on. That's the ground machine learning actually stands on, and it's the part most ML courses skip past in the rush to fit a model.
Before this I was a Chegg subject matter expert in probability and statistics. That matters here more than it sounds: almost every genuine difficulty in machine learning is a statistics difficulty wearing different clothes. Overfitting is a variance problem. Train-test splitting is a sampling problem. Every metric you'll be asked to justify in a viva or an interview is a conditional probability. Students who struggle with ML are usually struggling with the statistics they were never taught properly.
I'll be straight about scope: I teach foundations and applied fundamentals well. I'm not a deep learning researcher, and if you need cutting-edge work in that area I'll tell you so rather than take your money.
I've tutored math, statistics and programming since my undergraduate years, in English, Hindi and Tamil.
About the lesson
- College
- Masters/ Graduate School
- MBA
- +4
levels :
College
Masters/ Graduate School
MBA
Beginner
Intermediate
Advanced
Proficient
- English
All languages in which the lesson is available :
English
Most people learn machine learning backwards — they can call model.fit() within a week, and still can't say why their accuracy of 94% is meaningless. I teach it the other way round.
What we cover:
The foundations — what a model actually is, bias and variance, overfitting, train/validation/test splits, cross-validation, and why data leakage quietly ruins more projects than bad algorithms do
Supervised learning — linear and logistic regression, decision trees, random forests, gradient boosting, k-nearest neighbours
Unsupervised learning — k-means clustering, hierarchical clustering, PCA and dimensionality reduction
Evaluation — precision, recall, F1, ROC-AUC, confusion matrices, and choosing the metric that matches the actual decision being made
The unglamorous 80% — feature engineering, handling missing data, encoding categoricals, scaling, and dealing with imbalanced classes
Tools — Python, pandas, scikit-learn, matplotlib; R where your syllabus requires it
How I teach: every algorithm gets the intuition first, then the mathematics, then an implementation on real data. We work on messy datasets rather than the clean teaching ones, because clean data is the single most misleading thing about most ML courses.
Who this suits: BTech, MCA, MSc and MBA students with machine learning or data science papers; final-year students building ML projects; and working professionals who want foundations solid enough to build on rather than a certificate.
Also available for: project and capstone supervision, dissertation modelling chapters, and viva preparation — where the question is almost never "does it run" but "why did you choose that, and what would you do differently."
Recommendations
Recommendations come from relatives, friends and acquaintances of the tutor.
IT'S TRUE SAMRIDH IS A VERY GOOD TEACHER, HE ALWAYS SHARES HIS EXPERIENCE AND LEARNING . HIS EXPERTISE IN TEACHING MAKES YOUR LEARNING AT EASE. HE MAKE SURE THAT YOU UNDERSTAND THE CONCEPT ONE HUNDRED PERCENT. GOOD GOING BROTHER!
Classes with Samridh have been so worthwhile! He has an amazing way of breaking things down so that they are understandable, and always keeping it light and fun.
Samridh has excellence in conveying content into simple and easy term. His communication skills will be a great one for his ability of teaching.
A genius who can explain theories and problems with a practical explanation. Highly recommended.
He has good communication skills, and has in depth knowledge in his subjects, which helps in giving a enhanced knowledge about the subject. Has good coding skills and statistical analysis.
View more recommendations
Rates
Rate
- $17
Pack rates
- 5 h: $83
- 10 h: $158
free lessons
This first lesson offered with Samridh Vikhas will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hrs
online
- $17/h
Details
My standard rate is ₹1,200 per hour for online classes. No webcam fee, no travel fee, no materials charge. All code and notebooks from every session are yours to keep.
Packages:
5 hours — ₹5,750 (₹1,150 per hour)
10 hours — ₹11,000 (₹1,100 per hour)
For machine learning specifically I'd suggest the 10-hour package. Five hours is enough to cover a syllabus or fix a specific project; it isn't enough to build foundations from scratch, and I'd rather say that now than halfway through.
A note before you book: if your statistics is shaky, we'll spend the first session or two there. It's not a detour — it's the only thing that makes the rest stick, and skipping it is why so many people finish an ML course unable to explain their own results.
Free first class:
The first hour is free with no obligation. Send your syllabus, project brief or a description of what you're trying to build, and I'll come having read it. You'll get an honest assessment of how much time it will realistically take.
Payment:
After each session or at the start of a package, by UPI or bank transfer. Reschedules are free with a day's notice.
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