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ChrysCapital

ICICI Bank

HDFC

Nepean Capital

Innoeversity

Bajaj Finserv is the financial arm of the Bajaj group. The firm is currently engaged in life insurance, general insurance, and consumer finance businesses and has plans to expand its business by offering a wide array of financial products and services in India. The company is also active in a wind-energy generation. In 2020, the company recorded annual revenues of $7.8 B and a net profit of $497.3 M.

• Developed a real-time skeleton-based pose detection system using STGCN for surveillance applications.
• Optimized model with quantization and pruning for efficient edge device deployment.
• Implemented real-time inference using C++ and TorchScript for serialization.

BAAM.ECO

Sony Corporation is a multinational consumer electronics brand that designs and develops electronic equipment for consumer and professional markets. Their products range includes categories like cameras, mobile, tablet, smart devices, Televisions, home theater, audio products for home, Car &amp; marine and also gaming consoles. Sony is also into music & motion pictures production and financial services. Sony products retail out of their offline stores and through authorized online retailers. In 2020, the company recorded annual revenues of $79.9 B and a net profit of $10.1 B.In 2021, the company recorded annual revenues of $89.9B and a net profit of $7.99B

Developed a cutting-edge VAE-GAN pipeline to enhance low-quality video frames. By detecting drift and optimizing inference with TensorRT, we achieved a 30% improvement in object detection accuracy with YOLOv5.

A stealth startup is a startup company that operates in stealth mode, i.e. that avoids public attention. This may be done to hide information from competitors, or — as part of a marketing strategy — to manage public image. The phenomenon is well known in the venture capital (VC) community. Normally a company would only operate in stealth mode for the first couple of years. As investors may have to disclose funding a stealth startup, their names are made public, but often only a general summary description is known about the company. "Most entrepreneurs say they are in stealth because they are worried about competitors stealing their ideas. This can be a risk if you have such a simple idea that just by hearing it, someone can replicate it."​

• Developed automated text preprocessing pipelines for multilingual datasets to detect radicalization sentences on social media.
• Created a multimodal machine learning pipeline for emotion recognition from video, EEG, ECG, EDA signals, and transcript text data.
• Achieved high accuracy in classifying human emotions on arousal and valence scales.

World-leading research and technological innovation are an integral part of its DNA. Inria's 3,500 researchers and engineers put their passion for digital technology to work in nearly 200 project teams, most of which are joint teams with our academic partners, including major research universities and the CNRS. They explore new fields, often in collaboration with different disciplines and industrial partners, with the aim of meeting ambitious challenges.
 
As a technology institute, Inria supports the development of numerous software products, sometimes making a global impact via the opensource model. Because technology start-ups are powerful channels for research outcomes, Inria also supports entrepreneurial risk-taking and start-up creation (Deeptech). Firmly established on major university campuses and in industrial ecosystems, the Institute is at the heart of the digital revolution.

INRIA is the French National Institute for computer science and applied mathematics.

Worked on the project for Sq2Sq machine translation of indigenous Indian languages (Bengali, Tamil, and Telugu). I've used attention-based LSTM cell-based RNN encoder and decoder architecture to generate Indic language. We obtained an average BLEU score of 4.07, 5.43, and 4.97 for the respective languages trained on 25000 large text corpora

Worked on a project for stock market predictions using stacked LSTM based model and Fake news
classifier using bidirectional LSTM with 14.40 RMSE score and 90% accuracy - F1 both respectively.
Also, Build a Twitter Sentiment classifier using Machine learning algorithms which will give 94.3%
using Naive Bayes via TF-IDF vectorization(n-gram=2).

Naveen Penneru

Dalbir Singh Chhetri

Hemalatha Vinod Gandhi

Seema M Gandhi

Arpit Rajain

Nageshwara Rao

AI-based platform providing multi-disciplinary learning programs. The platform offers internship & degree courses such as web development, digital marketing, marketing, robotics, machine learning, and more.

AI-based platform providing multi-disciplinary learning programs

Senior Data Scientists @BajajFinserv | NLP | LLM | GenAI | Prompt Engineering | Computer Vision

Deepak Y

As a Senior Data Scientist at Bajaj Finserv, I have experienced in applying deep learning and NLP to solve complex problems and create innovative solutions. My work focuses on improving search relevance, enhancing query understanding, and developing intelligent systems like FAQ chatbots and code generation tools by using large language models (LLMs) to ensure seamless customer support.  I also bring extensive experience in computer vision, designing and optimizing object detection models while addressing challenges like data drift to ensure consistent performance across diverse datasets. Additionally, I leverage MLOps practices to streamline the end-to-end machine learning lifecycle, including model deployment, monitoring, and retraining, enabling scalable and production-ready AI systems.

Robust machine learning system designed to verify the accuracy of health-related claims. - deepak2233/fact-checking-health-data

GitHub - deepak2233/fact-checking-health-data: Robust machine learning system designed to verify the accuracy of health-related claims.

Developed end-to-end app to generate cartoons image description - deepak2233/Cartoon-Image-Generator-Using-VIT-And-GPT

GitHub - deepak2233/Cartoon-Image-Generator-Using-VIT-And-GPT: Developed end-to-end app to generate cartoons image description

merge raw embedding and graph based emending for better accuracy - deepak2233/Fake_News_Detection_Using_Graph_Neural_Network

GitHub - deepak2233/Fake_News_Detection_Using_Graph_Neural_Network: merge raw embedding and graph based emending for better accuracy

This model is created using pre-trained CNN architecture (VGG16 and RESNET50) via Transfer Learning that classifies the Waste or Garbage material (class labels =7) for recycling. - deepak2233/Waste...

GitHub - deepak2233/Waste-or-Garbage-Classification-Using-Deep-Learning: This model is created using pre-trained CNN architecture (VGG16 and RESNET50) via Transfer Learning that classifies the Waste or Garbage material (class labels =7) for recycling.

Semantic Segmentation using Unet. Contribute to deepak2233/Semantic-Segmentation-with-U-Net-for-Architectural-Data development by creating an account on GitHub.

GitHub - deepak2233/Semantic-Segmentation-with-U-Net-for-Architectural-Data: Semantic Segmentation using Unet

Deepak Yadav - HackMD

B.E at Chandigarh University - Cited by 7 - NLP - Computer Vision