Natural Language Processing

Auto-generate Kubernetes commands from plain English by leveraging the world’s most advanced language model.

Actions without Orchestration is just burnout; Kubernetes is an efficient orchestration of containers!

Pre-Requisites

  1. FastAPI — The Spiffy Way Beyond Flask!
  2. Streamlit — Revolutionizing Data App Creation
  3. A Brief Introduction to GPT-3

What is Kubernetes?


Auto-generate stock fundamental analysis from simple natural language inputs by leveraging the world’s most advanced language model.

“The most difficult thing is the decision to act, the rest is merely tenacity.” → Amelia Earhart

Pre-Requisites

  1. FastAPI — The Spiffy Way Beyond Flask!
  2. Streamlit — Revolutionizing Data App Creation
  3. A Brief Introduction to GPT-3

Fundamental Stock Analysis


Natural Language Processing

Auto-generate python code from simple natural language by leveraging the world’s most advanced language model.

Any sufficiently advanced technology is indistinguishable from magic — Arthur C. Clarke

Pre-Requisites

  1. FastAPI — The Spiffy Way Beyond Flask!
  2. Streamlit — Revolutionizing Data App Creation
  3. A Brief Introduction to GPT-3

The Promising GPT-3 — Is it the beginning of a new AI ecosystem?


Natural Language Processing

GPT-3 is transforming the way businesses can leverage AI to empower the existing products and come up with the next-gen of product offerings.

In this 21'st century, data privacy is not an option it’s a mandate…

Brief Overview 💡

In the above graph, it is clearly visible how GPT-3 dominates all the small models and gets substantial gains on almost all the NLP tasks. It is based on the approach of…


Natural Language Processing, Opinion

Generate creatively crafted professional marketing copies in minutes by leveraging the world’s most advanced language model.

Good ideas don’t require lots of other people to make them happen — GPT-3 version of Naval Ravikant

Pre-Requisites

  1. FastAPI — The Spiffy Way Beyond Flask!
  2. Streamlit — Revolutionizing Data App Creation
  3. Brief Introduction to GPT-3

GPT-3 v/s Human Brain


Natural Language Processing

OpenAI recently published a new successor to their language model, GPT-3, which is now the largest model trained so far with 175 billion parameters.

What fools call “wasting time” is most often the best investment — GPT-3 version of Nassim Taleb

What is GPT-3?

GPT-3 stands for Generative Pre-trained Transformer 3. It is an autoregressive language model that uses deep learning to produce human-like results in various language tasks. It is the third-generation of the language model in the GPT-n series created by OpenAI [1].

GPT-3 is an extension and scaled-up version of GPT-2 model architecture — It includes the modified initialization, pre-normalization, and reversible tokenization and shows strong performance on many NLP tasks in the zero-shot, one-shot, and few-shot settings.


Data Science, Programming

An elegant and efficient framework to build and share data apps within minutes.

Before starting let's get the fact straight — Every Data Scientist isn’t a good frontend engineer. But in the world where “seeing is believing”, the aesthetics of your project is as important as the technology behind it. What can you do in the situation when you have an amazing data app, but no frontend expertise to present it to a larger audience.

Streamlit to the rescue!

Streamlit is an open-source python library capable of turning data scripts into sharable web applications within minutes. It makes it very easy to build custom web applications with minimal efforts and zero knowledge of front-end design frameworks (all…


Natural Language Processing

Build Industrial strength Named Entity Recognition (NER) applications within minutes…

spaCy = space/platform agnostic+ Faster compute

Named Entity Recognition is one of the most important and widely used NLP tasks. It's the method of extracting entities (key information) from a stack of unstructured or semi-structured data. An entity can be any word or series of words that consistently refers to the same thing. Every detected entity is classified into a predetermined category. For example, a NER model might detect the word “India” in a text and classify it as a “Country”.

Many popular technologies that we use in our day-to-day life such as smart assistants like Siri, Alexa are backed by Named Entity Recognition. Some other…


Programming

An elegant and efficient framework to expose production-ready low latency APIs within minutes.

In recent times, there has been an exponential growth of data science and machine learning applications. With the advent of these data-driven applications, python is the go-to choice for most of the developers. In the last few years, python has jumped to the number one position for the languages used for ML which is mostly due to the convenience of packaging the models and exposing them as a service.

Model preparation and training is one of many steps in the machine learning lifecycle. Besides an active ML application, there go multiple things that work concurrently under the hood. On a…


Machine Learning

Efficiency is about doing better what’s already being done — Peter Drucker

MLOps is modeled on the existing discipline of DevOps, the modern practice of efficiently building, deploying, and running enterprise-grade applications to shorten the systems development life cycle and provide continuous delivery/deployment on the go with tested high-quality software.

As Machine Learning at an organization matures from research to applied enterprise solutions, there comes the need for automated Machine Learning operations that can efficiently handle the end-to-end ML Lifecycle.

In the initial phase of the evolving technological industry, the DevOps process paved the way for efficient management of the software development life-cycle. …

Shubham Saboo

AI @ Arcesium | Tech Leaders Fellow at Plaksha University | From Confusion to Clarity 🎯

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