“Pratima was part of our analytics team, a very valuable member, supported us in building and delivering LLM and NLP related products and services. She was smart and dedicated and always delivered high quality results. She was very creative and supported us in team engagement activities as well. I very much enjoyed having her on the team and would welcome any future opportunity to work together again!!”
About
I am passionate about Natural language processing, AI and deep learning. I am an…
Activity
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AI21Labs just released Jamba 1.5 Mini & Large - MoE, permissively licensed, 256K context, Multilingual, JSON model & Tool use 🔥 > Jamba 1.5 Large -…
AI21Labs just released Jamba 1.5 Mini & Large - MoE, permissively licensed, 256K context, Multilingual, JSON model & Tool use 🔥 > Jamba 1.5 Large -…
Liked by Pratima Rathore
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The frustration of manual prompting is real! But luckily, that stops today. We are officially in the age of auto-prompting. LLM task pipelines can…
The frustration of manual prompting is real! But luckily, that stops today. We are officially in the age of auto-prompting. LLM task pipelines can…
Liked by Pratima Rathore
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If you're like me, with terrible front-end skills! You're going to 😘 Vercel V0! 1 Prompt, 2 mins -> I had this react code ready! Relevant…
If you're like me, with terrible front-end skills! You're going to 😘 Vercel V0! 1 Prompt, 2 mins -> I had this react code ready! Relevant…
Liked by Pratima Rathore
Experience
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Education
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A comprehensive 11-month program taught by Industry experts and IIITB faculty; 10 case studies & projects; 400+ hours of academic learning & 30+ hours of industry mentoring
Consistently scored >90th percentile on all projects for data management, statistics, Datascience with python, predictive analytics, Machine Learning , Deep Learning and NLP courses -
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Licenses & Certifications
Volunteer Experience
Projects
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ANN-using-MNIST-dataset
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See projectbuilding a complete neural network using Numpy. You will use the MNIST dataset to train your model to classify handwritten digits between 0-9.
The code is divided into the following sections for better unnderstanding:
1.Data preparation
2. Feedforward
3.Loss computation
4.Backpropagation
5.Parameter updates Model training and predictions -
Heart Disease Prediction and Analysis using Random Forest
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See projectMachine learning (ML) proves to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry. This project is one such example in detecting whether a patient has heart disease or not based on some factors from their patient profile
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POS-Tagging-using-RNN
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See projectPOS Tagging using RNN Variants ( Vanilla RNN, LSTM , GRU , Bidrectional GRU)
We will be comparing the result in terms of accuracy , time and training parameters for different variants in POS tagging. -
Stock Price Case study using CNN-RNN
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See projectHere we have used a stock market price index data to implement the 1D CNN-RNN architecture
We'll try to model this relationship between the news and the stock market price of an index. Our assumption in modelling the stock price in this exercise is that news headlines that run on a particular day affect the opening stock price of an index the very next morning.
The important thing to keep in mind while doing this code,we will focus on the process of extracting textual features…Here we have used a stock market price index data to implement the 1D CNN-RNN architecture
We'll try to model this relationship between the news and the stock market price of an index. Our assumption in modelling the stock price in this exercise is that news headlines that run on a particular day affect the opening stock price of an index the very next morning.
The important thing to keep in mind while doing this code,we will focus on the process of extracting textual features using 1D CNN and then feeding them to an RNN.
Honors & Awards
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Wizard @work
Accenture
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Client value creation
Accenture
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Networking Guru
International Institute of Information Technology
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Top Performer
LJMU
Top Performer - Masters in Data Science LJMU | Cohort 8 | Dec 2019 - july 2022
Languages
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English
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Hindi
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Punjabi
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Recommendations received
7 people have recommended Pratima
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𝐒𝐞𝐥𝐞𝐜𝐭𝐋𝐋𝐌 - 𝐂𝐡𝐨𝐨𝐬𝐞 𝐎𝐩𝐭𝐢𝐦𝐚𝐥 𝐋𝐋𝐌𝐬 𝐟𝐨𝐫 𝐐𝐮𝐞𝐫𝐢𝐞𝐬 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐒𝐞𝐥𝐞𝐜𝐭𝐋𝐋𝐌? SELECTLLM is a novel algorithm…
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Meta Agent Search : Automated System Design Creation for LLM based Agentic Systems In this paper, authors formulate a new research area, Automated…
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Really stoked that I got a chance to a TEDx talk about AI! Thank you all coming for my TED talk! In my dreams :) This is a great moment! Not…
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BlackRock backed Groq. Try saying that 5 times fast. The AI chip maker is now valued at $2.8B and this $640M round of funding will help Groq deploy…
BlackRock backed Groq. Try saying that 5 times fast. The AI chip maker is now valued at $2.8B and this $640M round of funding will help Groq deploy…
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𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗻𝗴 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗟𝗟𝗠𝘀: 𝗔 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 Evaluating different Large Language Models (LLMs)…
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𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆: 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐬 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲 𝐚𝐧𝐝 𝐑𝐀𝐆 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞! The tech stack used for…
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My Low Level Technicals of LLMs 3 hour workshop is out! I talk about: 1. Triton vs CUDA 2. Why training is O(N^2) not cubic 3. GPT2 vs Llama 4. Why…
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Meta's Llama 3: The Llama 3 Herd of Models paper published today ... Meta's latest research paper, "The Llama 3 Herd of Models," marks a significant…
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