Sampreeth Raghu

• A driven professional with a strong background in software development with experience of 1 year.
• Now aspiring to transition into the dynamic and promising domain of data science. Showcasing a genuine passion for data science and its wide-ranging applications.
• actively engaged in extensive self-study and training, honing my skills in programming, analytical thinking, and effective problem-solving. Looking forward to work in data intensive industries.

Tittle : Stock Clue, Stocks Prediction Using Machine Learning 

• The project is driven to build an application for predicting the stocks using Machine Learning Algorithms and Python.

Purpose: The aim of Stock Clue is to forecast stock prices. A range of factors impact stock prices, such as market sentiment, economic statistics, and corporate updates. To anticipate upcoming stock price movements, your initiative leverages historic inventory statistics plus possibly other pertinent datasets.

Algorithm: RNNs excel when dealing with sequence data, such as stock price changes over time. Through time, these abilities allow them to identify patterns and correlations within data. LSTM, a subtype of RNNs, has become prominent in stock price predictions thanks to its capacity to process extended patterns found within massive databases.

Model Building: A unique feature of LSTM is the ability to retain information about lengthy patterns in sequential data. Past performances have significant impact on anticipated future ones, emphasizes the importance of understanding historical data in predicting stock movements. With help from LSTMs, complicated relationships become more understandable.

 Artificial Intelligence and Machine Learning ,   Tequed  Labs, Bangalore

 Sept 2021

• At Tequed Labs and research for Innovation, I had the opportunity to acquire valuable knowledge in Artificial Intelligence and Machine Learning Technology. Through my experience there, I delved into the intricacies of these cutting-edge fields and gained a deep understanding of their principles and applications
• My experience at Tequed Labs and research for Innovation provided me with a solid foundation in AI and
  ML. It equipped me with the necessary skills and knowledge to apply these technologies to drive innovation
  and make a significant impact in the fields.

Traffic Prediction for Intelligent Transportation using Machine Learning

Purpose: Traffic flow prediction is one of the key problems in traffic control and guidance system as well as the important functions of intelligent transportation system.

Algorithm: 

• Random Forest Algorithm is better predictive and accuracy can use for both classification and regression problems Gives highly accurate predictions Powerful than other non-linear models.
• The Random Forest algorithm has the characteristics such as high robustness, performance and practicability. The weather conditions, time period, special conditions of road, road quality, vehicle count are used as model input: variables to establish traffic prediction system.

Model Building 

• Bellman-Ford algorithm as a shortest path algorithm by considering the measurement of travel time instead of the distance between edges in the graph
• YOLO Model: This is a real-time monitoring system in our system, here is a video taken from our input road. The video is sent to the YOLO (You only Look once) algorithm for object detection.

• Data Science Program - NIIT Limited , 365 Data Science
• Certificate For Completion Of Artificial Intelligence - Great Learning
• Certificate For Completion Of Python Programming - Great Learning
• Career Edge ION Program - TCS ION