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A single hackathon teaches you greater than any e book or course: MachineHack Grandmaster Tapas Das

MachineHack Grandmaster Tapas Das is a Knowledge Engineer with over 9 years of expertise constructing scalable, optimized and customer-centric IT options. The Kaggle Notebooks skilled has participated in 32 MachineHack hackathons and is a prime 10 world champion.

“I can solely work successfully if there are few or no distractions. So for me, stepping into the Zone is just about simply sitting in a nook with my laptop computer, headphones on, and blasting rock steel at full quantity. I would like music to prepare my ideas and discover higher options,” mentioned Tapas Das, Supply Supervisor, The Math Firm.

Analytics India Journal reached out to this alpha geek for perception into his knowledge science journey and hackathon exploits.

AIM: How did your fascination with algorithms come about?

Tapas Das: I first took an interest on this subject in 2018, after coming throughout an article about how Google Search predicts consumer searches so successfully. After that, I began researching machine studying and the way totally different algorithms work. Then I went by means of totally different MOOCs just like the “well-known” Andrew Ng ML course and the Deep Studying Specialization course on Coursera.

AIM: What have been the preliminary challenges and the way did you overcome them?

Tapas Das: I had a really clear intention after I began the ML journey. I wished to construct a machine studying mannequin from scratch with out utilizing widespread frameworks like PyTorch, Tensorflow, Caffe, and many others.

I spent a number of time studying and coding the fundamentals of ML like perceptron, ahead propagation, backward propagation, gradient descent, and many others. Then I constructed a primary neural community classifier to categorise canine versus cats. Though it took two complete days to follow, with none of the GPU optimizations, the ultimate 75% accuracy was the “Eureka” second for me.

AIM: What excites you essentially the most about coding?

Tapas Das: I’ve at all times been fascinated by totally different programming languages. I began out coding in C and ultimately switched to Python. The world I am most enthusiastic about is the handshake between software program and {hardware} – how can we write extra environment friendly code to make use of minimal {hardware} sources and run in milliseconds.

OBJECTIVE: What does your ML software stack seem like?

Tapas Das: Effectively, it relies on the ML downside we try to resolve. I at all times begin with fundamentals like Linear Regression or Elastic Web if it is a regression downside, or Logistic Regression or SVM if it is a classification downside. Then, I slowly evolve in the direction of tree fashions (Random Forest, XGBoost, LightGBM) or neural networks (Tensorflow or Keras).

When it comes to libraries, scikit-learn is sort of a godsend and has at all times been my favourite library. I rely closely on FeatureTools for function engineering and Optuna for hyperparameter analysis.

AIM: Find out how to put together to your first hackathon?

Tapas Das: For anybody beginning the “ML hackathon” journey, my suggestion could be to start out by studying EDA. The extra you perceive the information and the area, the clearer you might be when engineering options or choosing options.

I typically desire to do all EDA manually as an alternative of counting on auto-EDA libraries like SweetViz or Pandas-Profiling. This helps to get higher insights into the information by adjusting the visualizations as wanted. I depend on Matplotlib and Seaborn to construct the visualization.

AIM: What’s your largest pet peeve about hackathons?

Tapas Das: Knowledge leak! It’s driving me loopy. This makes the entire rating mindless, after which everyone seems to be competing to optimize for the 4th or fifth decimal of the metric.

AIM: What drew you to MachineHack? Inform us about your journey to this point.

Tapas Das: I have been taking part in several hackathons on the MachineHack platform for some time now, and I really like how the platform permits anybody, no matter background or earlier expertise, to compete on equal footing the place typically the one factor that issues is optimizing a metric.

Successful options from earlier hackathons are a useful studying useful resource that I strongly encourage budding individuals to faucet into. Doing a single ML hackathon teaches you greater than any e book or course. It is enjoyable to compete with the best minds in knowledge science.

AIM: What was your first MachineHack competitors like?

Tapas Das: I’ve participated in 32 hackathons to this point on Machine Hack. However it began with the “Predicting Meals Supply Time” hackathon. Being a noob, it was a shock to take part in my first ML hackathon and fail gloriously within the leaderboard.

Subsequent, I totally analyzed the winner’s method to fixing this hackathon to evaluate my weak factors. I used to be blown away by the individuality and revolutionary high quality of every successful resolution.

AIM: How did you are feeling while you turned a grandmaster of Machinehack?

Tapas Das: After I turned a grandmaster, the sensation was just like the final counselor in class fixing an issue that even the very best college students failed to resolve. I can not describe it another means. It’s a combination of pleasure, ecstasy, shock and shock.

PURPOSE: Ideas for Profitable MachineHack.

Tapas Das: Be very enthusiastic about what you do, keep motivated even should you do not do effectively in some hackathons, and continue learning and exploring totally different approaches. In the end, your efforts will repay.

As Eminem, rapped:

“You higher get misplaced within the music, the second

You personal it, you higher by no means let it go

You solely get one hit, do not miss your probability to blow

This chance solely comes as soon as in a lifetime yo!”

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