A collection 📁 my all Certificates 🎖️.
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Updated
Jul 5, 2024
A collection 📁 my all Certificates 🎖️.
Built a predictive machine learning model using a Streamlit application to predict weekly sales. Model achieved 97.4% accuracy and analyzed trends, patterns, and data insights using EDA. Compared various features and identified key contributors with a significant impact on prices.
Unleash the power of AI in your terminal with Clara ! 🌟 Revolutionising script automation with GPT-3.5 (and soon, GUVI-GPT & Llama2), this tool is a game-changer for developers who crave efficiency with a dash of fun. Whether you're coding in Python 🐍, planning for Go, or scripting in JavaScript, let AI do the heavy lifting.
This web application was created according to the software requirements given in the Problem Statement on GUVI - Intern for web developer role.
Here, I Understand how React Router works to manage navigation within a React application
Collecting YouTube data using google API and storing the data in MongoDB(NoSQL) and Migrating the stored data from MongoDB into SQL and creating a user friendly Streamlit web app for the visualization and to get a better understanding of the YouTube channels and video details. All with the help of Python and Python libraries.
Collection of DSA questions from competitive coding websites and simple and basic data structures to ace the coding interview!
Codekatas typically involve writing code to solve a specific problem, and the goal is to write efficient, working code that meets the requirements of the problem statement. In this repository you can find the python programs which is related to arrays.
Codekatas typically involve writing code to solve a specific problem, and the goal is to write efficient, working code that meets the requirements of the problem statement.
Codekatas typically involve writing code to solve a specific problem, and the goal is to write efficient, working code that meets the requirements of the problem statement. In this repository you can find the python programs which is related to arrays.
This project aims to predict customer conversion for an insurance company. Using historical data, we will develop a machine learning model that can identify which customers are most likely to purchase a policy. By understanding the patterns and behaviors of previous customers, the model can make predictions and provide valuable insight to company.
In this repository you can find the examples of Logistic Regression , K-NN, Decision Tree, Random Forest algorithms.
This repository is related to pandas library. in this you can find around 60 questions with answers.
Repository containing the colab-notebooks of the course i did on deep learning from One-Fourth-Labs
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