Name: Sandeep Kumar Kushwaha
Type: User
Company: Wenda srl
Bio: AI Expert exploring GenAI and LLMs, with expertise in NLP, Multimodals, Transformers, Deep Learning and Machine Learning.
Location: Bologna, Italy
Blog: https://www.linkedin.com/in/xandie985/
Sandeep Kumar Kushwaha's Projects
The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area, at road level,within an Italian city.
Animal Center Outcomes from Oct, 1st 2013 to present. Outcomes represent the status of animals as they leave the Animal Center. All animals receive a unique Animal ID during intake. Annually over 90% of animals entering the center, are adopted, transferred to rescue or returned to their owners.
sentiment_analysis_Naive_Bayes_,_BERT_&_RoBERTa
Sentiment Extraction on Social media texts related to Cryptocurrencies.
Caffe: a fast open framework for deep learning.
image classification task
Project work for Artificial Intelligence in Industry
A genetic algorithm is a search heuristic that is inspired by Charles Darwin's theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.
In this project we will work on the captions, hastags, image tokens, location & time into consideration to enhnace the Engangement Ratio.
The source codes for Fine-grained Fact Verification with Kernel Graph Attention Network.
We have used Data Processing and training the Linear Regression model to predict the stock market for the next day. This model performs with around 70% accuracy.
The following codes are in numpy and python meant for beginners.
A ClojureScript framework for building user interfaces, leveraging React
scikit-mobility: mobility analysis in Python
Here I will create a weapp that helps in managing tasks via simplified web page. I will use Heroku to deploy the model.