Schools of Thought in Deep Learning 🏫🎒💭
The Belamy | The weekly newsletter of Analytics India Magazine
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1
Big Tech & Their Favourite Deep Learning Techniques
Every week, the top AI labs globally — Google, Facebook, Microsoft, Apple, etc. — release tons of new ML research work, tools, datasets, models, libraries and frameworks.
Interestingly, they all seem to have picked a particular school of thought in deep learning. With time, this pattern is becoming more and more clear. For instance, Facebook AI Research (FAIR) has been championing self-supervised learning (SSL) for quite some time.
2
Is Apple Near Its Saturation Point In CPU Advancements?
The recent virtual event by Apple, popularly called “California Streaming”, has come to an end. An unusual trend can be spotted.
Instead of comparing the newly introduced A15 Bionic chip to the previous generation (A14, A13…) like they usually do, they opted to compare to ambiguous “competitors.”
This points towards an interesting thing to figure out — does the newly introduced A15 have few advancements to show with respect to its predecessor, the A14 chip?
3
Jupyter Labs Desktop App: Do We Need It?
JupyterLab App is “the cross-platform standalone application distribution of JupyterLab. It is a self-contained desktop application which bundles a Python environment with several popular Python libraries ready to use in scientific computing and data science workflows.”
Up until now, JupyterLab has been maintained in the environment within a web browser, but as per the latest updates, it is a standalone application.
4
Sketch Note of the week
5
How I created An AutoML Library
Deep_AutoViML is an extension of Ram Seshadri’s past open-source libraries; AutoViz, Auto-TS and Auto_ViML. AutoViz is his library to help visualise data sets automatically with a single line of code; Auto_ViML is to automate building pipelines in a single line of code, used especially for hackathons & exploratory model building and Auto-TS for time series models in a single line of code.
6
Hands-on Guides for ML Developers
+ How to Visualize and Debug Machine Learning Models using ELI5?
+ Django vs Flask vs FastAPI - A Comparative Guide to Python Web Frameworks
+ A Guide to Different Types of Noises and Image Denoising Methods
+ A Comprehensive Guide to Maximum Likelihood Estimation and Bayesian Estimation
+ Are Larger Language Models Less Truthful?
7
PEOPLE & STARTUPS
+ India’s Top Ethical AI Advocate: The Journey Of Saishruthi Swaminathan
+ Exciting Times For AI in India: Sameep Mehta, Lead - Data and AI Platforms, IBM Research India
+ Virtual Tour With Harshit Agrawal, Man Behind India’s First Solo AI Art Show
+ Interview With Sanmay Das, Chair, ACM’s Special Interest Group on AI
+ How Coverfox Utilises Machine Learning
+ Are No-Code Platforms Suitable Partners for Businesses? Hubbler CEO Discusses
8
Apple & Neural Network Subspaces?
Apple’s machine learning team has recently showcased their work on neural network subspace at this year’s ICML conference. In this work, the researchers showed how neural network subspaces contain diverse solutions that can be used to train neural networks without the training cost independently.
9
Postman’s New API Platform
Recently, Founder and CEO of Postman, Abhinav Asthana took to its blog to release an upgraded version of its API platforms.
Its latest version of the API platform combines the different tools and processes into one definitive. Founder and CTO Ankit Sobti shares the major six upgrades in his latest blog post.
10
BOTTOM OF THE NEWS
Here's what all happened last week.
+ Accenture Surpasses $50 Billion Annual Revenue, Posts Robust Q4 FY21 Results
+ Ex-Apple Employee Exposes Apple M1 Chip's Secrets
+ Toshiba Claims To Have Created World’s Most Accurate Visual Question Answering AI
+ Salesforce Open Sources CodeT5: An ML Model That Generates Code
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