Data Science Interview Guide
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Data Science Interview Guide

This is a practical guide to help you ace classical Machine Learning interviews.

About the Book

The book contains sample of theoretical questions asked on interviews on Data Science position.

What you will get:

  • 6 chapters 47 pages covering topics ranging from Statistics and probability, Supervised machine learning, Gradient Descent Algorithm, Loss measure
  • 77 interview questions
  • Usefull links and preparation repository

About the Author

Alimbekov Renat
Alimbekov Renat

Hello everyone, my name is Renat Alimbekov. I work as a Big Data Analyst at Beeline Kazakhstan.

Previously I worked as a Deep Learning Scientist at an AI medical startup. I have done research and work with medical data and images. In addition, I work as a mentor at Yandex.Practicum. I help students to master the Data Scientist profession.

I have my own blog and telegram channel where I write guides and practical advice on Data Science and Machine Learning.

I take part in competitions on the kaggle site (profile). I am a repeated high ranking competitor, including in competitions with medical data: SIIM-ACR Pneumothorax Segmentation, RSNA Intracranial Hemorrhage Detection, Prostate cANcer graDe Assessment (PANDA) Challenge, RANZCR CLiP - Catheter and Line Position Challenge

I also rank 17th and 95th in the CheXpert Stanford ML Group competition.

You can support me to create new courses and other content on Patreon.

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