NAMAN GUPTA

Detail-oriented, organized, and meticulous employee with a proven track record of working efficiently under pressure to meet tight deadlines. Dedicated team player enthusiastic about collaborating with colleagues to achieve company success. Eager to leverage skills and experience to make a positive impact within the organization.

• Bharat Internship in Data Science
• Project 1 : Titanic Classification in python - To perform Titanic classification in Python, you can use a machine learning approach to predict whether a passenger survived the Titanic disaster based on features like age, gender, class, and others. Below is a step-by-step guide to solving this classification problem using the Titanic dataset.
• Project 2: Stock Prediction - Stock prediction is a complex task that involves forecasting the future prices of stocks based on historical data. It's an area that often uses machine learning techniques to identify patterns in the market and predict future trends. Below, I will guide you through a simple stock prediction using Python. We'll use historical stock data and a machine learning model to predict the stock price.
• Bharat Internship in Machine Learning
• Iris Flowers Classification: The Iris Flowers Classification problem is a classic example in machine learning, where the goal is to classify the type of iris flower based on the following features:
• Sepal Length
• Sepal Width
• Petal Length
• Petal Width
• Project 2 : Wine Quality Prediction - Wine quality prediction is a popular machine learning classification problem where the goal is to predict the quality of wine based on several physicochemical features such as alcohol content, acidity, sugar level, etc. The dataset typically consists of various chemical properties of wines and their corresponding quality ratings.

We will use the Wine Quality Dataset available in the which contains two versions:

• Red wine dataset
• White wine dataset

The dataset consists of several features like alcohol content, volatile acidity, residual sugar, etc., and the target is a quality score ranging from 0 to 10.

• AI EMPOWERED CARRER MANAGEMENT SYSTEM .
• An AI-empowered Career Management System uses artificial intelligence (AI) to help individuals and organizations manage career growth, recruitment, skill development, job matching, and career transitions. This type of system leverages AI algorithms, machine learning models, and data-driven insights to offer personalized, automated, and more efficient career management solutions.
• Human AI collaboration
• Job Market Insights
• Personal Recommendation.
• OBJECTIVE : The overarching objective is to enhance career growth and recruitment processes by leveraging AI to provide personalized, data-driven, and automated solutions that benefit both individuals and organizations. This results in smarter career development, better job matching, optimized recruitment, continuous learning, and seamless transitions, all guided by insights derived from data and AI models.
• METHODOLOGY : Problem identification and requirment Analysis.
• Data Collection and Processsing
• Machine Learning model development
• CONCLUSION: An AI-empowered Career Management System has the potential to revolutionize how individuals and organizations approach career growth, job matching, and talent development. By leveraging AI technologies like machine learning, NLP, and predictive analytics, these systems can provide personalized, data-driven career support that adapts to changing market conditions and evolving personal goals.

• FULL STACK in JAVA From CODING NINJA.