Artificial Intelligence

2023-05-31 07:21:40 Industry Data Science vs Academia Data Science

Comparing Data Science in academia and Data Science in industry is like comparing tennis with table tennis: they sound similar but in the end, they are completely different!

5 big differences between Data Science in academia and in industry :

Model vs Data: Academia focuses on models, industry focuses on data. In academia, it’s all about trying to find the best model architecture to optimise a defined metric. In industry, loading and processing the data accounts for around 80% of the job.

Novelty vs Efficiency: The end goal of academia is often to publish a paper and to do so, you will need to find and implement a novel approach. Industry is all about efficiency: reusing existing models as much as possible and applying them to your use case.

Complex vs Simple: More often than not, academia requires complex solutions. I know that this isn’t always the case but unfortunately, complex papers get a higher chance of being accepted at top conferences. In industry, it’s all about simplicity: trying to find the simplest solution that solves a specific problem.

Theory vs Engineering: To succeed in academia, you need to have strong theoretical and maths skills. To succeed in industry, you need to develop strong engineering skills. It is great to be able to train a model in a notebook but if you cannot deploy your model in production, it will be completely useless.

Knowledge impact vs $ impact: In academia, it’s all about creating new work and expanding human knowledge. In industry, it is all about using data to drive value and increase revenue. (credits: unknown)

Anything else missing? Let me know Open / Comment

2023-05-30 05:48:31 Use Chatgpt to prepare a PowerPoint Presentation

Prompt:
“I want you to write me VBA code for a PowerPoint presentation about the history of AI. You are to fill in all the text with your own knowledge, no placeholders. I need 5 slides.” Open / Comment

2023-05-23 21:44:27 Adobe introduces Generative AI fill in Photoshop!

It's a beta app right now to unleash your imagination as you can generate extraordinary images from a simple text prompt.

The only limit is our imagination in creating fabulous images with these flooding AI apps. Open / Comment

2023-05-19 12:35:53 Photoshop is finished?

Imagine being able to perfect any picture exactly how you want it.

Now it's as simple as drag and drop with this AI:

Researchers from Max Planck Institute for Informatics, MIT and Google have developed DragGAN.

It lets you 'drag' any part of a picture to exactly where you want it.

DragGAN has 2 main parts:
• Motion supervision — this guides the point you're moving towards the target position
• Point tracking — this uses special features to keep an eye on the point you're moving

This means it can make really realistic changes, even for difficult tasks like creating hidden parts of images or changing shapes while keeping them looking natural.

Where Photoshop often requires intricate skill and knowledge, DragGAN makes complex edits as simple as drag and drop.

While DragGAN excels at precise image deformation, I still feel Photoshop's comprehensive tools for graphic design hold value.

Code: https://github.com/XingangPan/DragGAN
Paper: https://huggingface.co/papers/2305.10973 Open / Comment

2022-08-31 16:15:00 There has never been a better or more exciting time to work in AI and deep learning... Open / Comment

2022-08-31 10:26:01 https://www-deccanherald-com.cdn.ampproject.org/c/s/www.deccanherald.com/amp/national/indian-armed-forces-aiming-to-go-big-with-artificial-intelligence-1125123.html Open / Comment

2022-08-28 17:42:06 Want to get into Data Science?

Internet is free university.

Here are the free resources to learn

Coding: https://bit.ly/3dJXEou
SQL: https://bit.ly/3K6Y9Fn
Data Analysis: https://bit.ly/3QRJsIA
Machine Learning: https://bit.ly/3R1who6
Deep Learning: https://bit.ly/3KdxNkX
Visualisation: https://bit.ly/3R0eaiq
GitHub: https://bit.ly/3Qy5lN7
AWS: https://go.aws/3KbVfyV

You don't lack resources.

You just need a laptop and internet connection.

No more excuse. Open / Comment

2022-08-07 18:04:11 Image segmentation is the process of partitioning a digital image into multiple segments.

Learn how it works and get started here >>> https://www.tensorflow.org/lite/examples/segmentation/overview?linkId=8139418 Open / Comment

2022-08-06 18:00:27 How Alibaba Use Artificial Intelligence and Machine Learning

Alibaba is using AI to optimize its supply chain, drive personalized recommendation, Chatbots and build products. It also provides cloud-based AI service, to know more read the Blog

Checkout the Twitts

. Open / Comment

2022-07-28 17:37:27 The best Stanford, CMU, and MIT courses to build a career in AI

- With a multitude of AI courses available online, coming up with an AI study plan can easily lead to decision fatigue.
- I often get asked about which courses have been useful to me to setup my foundation in AI, so here goes!
- After taking Stanford’s AI courses to build my fundamentals, I’ve taken courses from CMU, MIT, and UCL. I’ve found these pretty useful in shaping my understanding and career in AI.
- Here’s my list of courses along with their respective YouTube playlists (note that this is an ordered list of increasing difficulty, based on my personal experience) by Aman Chadha.

Stanford University

CS229 - Machine Learning by Andrew Ng: https://m.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
CS230 - Deep Learning by Andrew Ng: https://m.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb
CS231n - Convolutional Neural Networks for Visual Recognition by Fei-Fei Li and Andrej Karpathy: https://m.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv
CS224n - Natural Language Processing with Deep Learning by Christopher Manning: https://m.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ
CS25 - Transformers United: https://m.youtube.com/playlist?list=PLoROMvodv4rNiJRchCzutFw5ItR_Z27CM

Massachusetts Institute of Technology

6.S191 - Introduction to Deep Learning by Alexander Amini and Ava Soleimany: https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI
6.S094 - Deep Learning by Lex Fridman:
https://m.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf
6.S192 - Deep Learning for Art, Aesthetics, and Creativity by Ali Jahanian: https://m.youtube.com/playlist?list=PLCpMvp7ftsnIbNwRnQJbDNRqO6qiN3EyH

Carnegie Mellon University
CS/LTI 11-777 Multimodal Machine Learning by Louis-Philippe Morency: https://m.youtube.com/channel/UCqlHIJTGYhiwQpNuPU5e2gg/videos

University College London
COMP M050 Reinforcement Learning by David Silver:



- Have courses that you found useful? Drop me a message @Aiindian so I can learn too! Open / Comment