New research paper by Facebook on End-to-End Object Detection with Transformers
https://research.fb.com/publications/end-to-end-object-detection-with-transformers/
https://research.fb.com/publications/end-to-end-object-detection-with-transformers/
Meta Research
End-to-End Object Detection with Transformers - Meta Research
We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many...
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Coding and Aptitude Round before interview
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world.
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world.
👍3
Data science use cases in finance
https://www.kdnuggets.com/2018/05/top-7-data-science-use-cases-finance.html
https://www.kdnuggets.com/2018/05/top-7-data-science-use-cases-finance.html
KDnuggets
Top 7 Data Science Use Cases in Finance - KDnuggets
We have prepared a list of data science use cases that have the highest impact on the finance sector. They cover very diverse business aspects from data management to trading strategies, but the common thing for them is the huge prospects to enhance financial…
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Udemy
Online Courses - Learn Anything, On Your Schedule | Udemy
Udemy is an online learning and teaching marketplace with over 250,000 courses and 80 million students. Learn programming, marketing, data science and more.
Forwarded from Jobs | Internships | Placement | Interviews
Looking for Data Scientists to work as Teaching Associates(10 positions)1-6 years exp .
Benglore based
Please share cvs on Renu@marketscope.in
9-13L CTC
Benglore based
Please share cvs on Renu@marketscope.in
9-13L CTC
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Udemy
Online Courses - Learn Anything, On Your Schedule | Udemy
Udemy is an online learning and teaching marketplace with over 250,000 courses and 80 million students. Learn programming, marketing, data science and more.
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Udemy
The Complete Introduction to Data Analytics with Tableau
Kickstart your Data Analytics Career with Tableau by solving Realistic Analytics Projects. Learn Data Visualisation!
Which is not a type of machine learning
Anonymous Quiz
3%
Supervised Learning
8%
Unsupervised
83%
Inforcement Learning
6%
Reinforcement Learning
👍2
In which machine learning algorithm, machine learn on its own
Anonymous Quiz
33%
Supervised Learning
67%
Reinforcement Learning
👍1