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"Ads-Click-Through-Rate-Prediction" is a data-driven approach to forecast the likelihood of users clicking on online advertisements, aiding marketers in optimizing ad campaigns for maximum engagement and conversion rates.
License: MIT License
ads-click-through-rate-prediction's Introduction
Hi there! 👋
I'm Rahul Bhoyar , a passionate AI and Software Proffessional from Berlin.
🔭 I’m currently a student at Internatinal University of Applied Sciences, Berlin .
🔭 I am currently pursuing MBA in Artificial Intelligence .
🌱 I’m currently working on several Generative AI projects.
👯 I’m looking to collaborate on Generative AI projects.
AI Tech stack : Generative AI, LLMs, Natural Language Processing, Deep Learning, Machine Learning, Data Science, Data Analytics
Programming Languages: Python, SQL, R
Deployment Tools : HuggingFace, Streamlit Cloud, Heroku
Web Technologies (Back-end): Streamlit, Django, Django REST, Flask, Gradio
Web Technologies (Front-end): HTML, CSS, JavaScript.
Web Scraping : Selenium, Scrappy, Beautiful Soup
Data Analysis : Pandas, Numpy
Geographical Data Analysis : Folium, Geopandas
Data Visualisation : Matplotlib, Seaborn, Plotly
Machine Leanring Libraries : Sklearn
Deep Learning Libraries : Tensorflow, PyTorch
Containerisation Tools : Docker and Kubernetes
Cloud : Google Cloud, Microsoft Azure, AWS
Repo Management : Git, Gitnash, Github, Gitlab, Bitbucket
OS System Environment : Windows, Linux, iOS
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