Israr Ahmad
@iDoswi1MS in Pattern Recognition, looking for PhD position in Machine Learning/Deep Learning and Computer vision.
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🤔Experiencing imposter syndrome as a PhD applicant. I'm applying to professors with 80-90% aligned research interests, and their open announced positions, yet no responses so far. Could someone kindly review my documents and offer suggestions if there are any issues? Thanks 🙏
Despite near-perfect research alignment and advertised openings, why do some potential supervisors consistently ghost PhD/postdoc candidates? (no disrespect to respected Professors just asking) This perplexing trend is all too common. @CSProfKGD
Machine learning algorithms in under a minute. #ML #AI #TensorFlow #PyTorch #Algorithms aboutprogrammingtrends.blogspot.com/2022/08/machin…
Life of introverts.
The easiest thing from below is dreaming, and the most difficult is staying focused.
Be nice to others and follow this guide for a happy and productive life!
A common point raised by ML reviewers is that a method is too simple or is made of existing parts. But simplicity is a strength, not a weakness. People are much more likely to adopt simple methods, and simple ones are also typically more interpretable and intuitive. 1/2
First Principles of Computer Vision, Columbia University Really nice lectures on the physical and mathematical foundations of computer vision. 140 videos that you can watch at your pace. Slides are also provided to follow along.
Computers in 1962. 😊
My research group @Mila_Quebec is such a great place to work at - amazing humans 🥰 They are so supportive and also celebrate one another’s success.
Information theory, control theory, game theory, optimization/deep networks, machine learning, and statistical learning, all work on the same set of ideas of intelligence, just different pieces, and definitely with different terminologies.
A Superhuman I guess. 😃
There is this argument that the larger the network model is and the more memorized data/tokens, the better the performance. Well, I want to remind everyone that the largest network is the InterNet. I believe we all experience (or suffer) how intelligent it is, or a lack thereof.
Don't work on a project in your PhD if a technician can do it. Pick projects that are intellectually challenging and require deep thinking
A lot of people seem to be curious: how do you choose which research problems to work on?
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