Skip to main content

The Project Based Internship: with MentorBruh

Introduction:

Hi, welcome to the internship page! from 2020, we are launching an intense practical project based machine learning internship from MentorBruh.
 
Potential candidates:
 
While there is no bar for any streams and years to try and avail the internship; we are currently looking for students with
(a) basic knowledge of coding in python/java
(b) preferred knowledge of exploratory statistics, basic machine learning algorithms
(c) tenacity to actively learn the hard stuff, present and be vocal about their achievements 
(d) principles about time, commitment and team-activity

Types of content in internship:

The internship we are offering will be hands-on with real projects, will simulate office projects, with proper literature research, coding or code explorations, and presenting deliverables within short timeframes. 
To clarify beforehand, we will not teach you anything from scratch, but live doubt sessions will be arranged whenever suited for the growth of project.
The end goal of this internship is to 
(a) provide a student specialty angle in one or more side of machine learning, hence dramatically increase their chance of getting hired.
(b) equip a student with presentation skills needed to kill hr and technical rounds without shred of self doubts or ambiguous knowledges
(c) complete quality projects to showcase in CV for at least upto 2-3 years into data science domain.

What we don't do here:
(a) We don't mentor in bulk. We have only (<10) very few seats available; and provide a purely personal mentoring. 
(b) We don't pay or get paid for all the work that will be done. All the mentoring will be done; free of cost, and your codes will not be provided to another party for running third party applications. Only in special scenario, we may showcase some of your projects as affiliate marketed contents. 
(c) We don't teach courses here. While from this domain you can read variety of posts on different machine learning topics; and/or will be referred to read when/if necessary; that is not a part of the internship.

 
Final point:

If you think you are not moving in correct direction of getting hired in the correct firms instead of you having the correct potential; this is where you will get the special edge to stand out. Mail us at shyambhu20@gmail.com and we will get shortly in contact with you. 
 

Popular posts from this blog

20 Must-Know Math Puzzles for Data Science Interviews: Test Your Problem-Solving Skills

Introduction:   When preparing for a data science interview, brushing up on your coding and statistical knowledge is crucial—but math puzzles also play a significant role. Many interviewers use puzzles to assess how candidates approach complex problems, test their logical reasoning, and gauge their problem-solving efficiency. These puzzles are often designed to test not only your knowledge of math but also your ability to think critically and creatively. Here, we've compiled 20 challenging yet exciting math puzzles to help you prepare for data science interviews. We’ll walk you through each puzzle, followed by an explanation of the solution. 1. The Missing Dollar Puzzle Puzzle: Three friends check into a hotel room that costs $30. They each contribute $10. Later, the hotel realizes there was an error and the room actually costs $25. The hotel gives $5 back to the bellboy to return to the friends, but the bellboy, being dishonest, pockets $2 and gives $1 back to each friend. No...
Post a Comment
Read more

Deep Learning by Ian GoodFellow, Yoshua Bengio and Aaron courville Review

History: I have been reading deep learning topics from a number of resources like machine learning mastery by Jason Brawlee, Analyticsvidhya, and other blog resources. But the problem has stayed, the problem of inconsistency in the knowledge. Therefore, I have decided to now sit down, and go through a deep learning book thoroughly. And what better name for deep learning other than Ian Goodfellow! So I have found this book named Deep Learning by Ian Goodfellow. Introduction: Plan for this post is reviewing and rewriting the topics from the book, in simpler language and for sharing the pieces of knowledge with my readers. I will update this post continuously as I proceed with the reading also. So ideally this post is broadly about basic to advanced deep learning material discussion. Sponsored Ads Learn deep learning in python with Udemy   Different parts of the book and purpose of them: This book has three parts,which talks about (1) applied mathematics and machine learni...
Post a Comment
Read more

Pyarabic: python package for Arabic language

 Introduction:  In languages which are non-english and non-european as well, NLP work has progressed slowly in the last few decades because of the lesser number of scholars working on them as well as a lack of global interest in them. But now the time has changed and people from all over the world are collaborating on these lesser explored libraries and they are building resources for working on these languages with the same ease with that of english.  Pyarabic is a package created from such a similar effort which deals with the intricate details of the arabic language and helps processing all kinds of arabic texts. While trying to learn it, being from a non-arab background, I couldn't read lots of parts of the main readthedocs site and had to work my around it. So in this blog post, I will summarize my learnings in english language, so that you can learn it and use the package with much more ease than me. [Credit where credit is due: this article heavily uses the ac...
Post a Comment
Read more