Anand P

Highly-motivated individual with desire to take on new challenges. Strong work ethic, adaptability and good interpersonal skills. Adept at working effectively unsupervised and quickly mastering new skills. Skilled at identifying patterns, relationships and trends within data or information.

• Sequential Natural Language Processing : Part 1 - Implementing a sequential NLP based text classifier, for a company in digital content & entertainment industry, using input text parameters to determine the customer's sentiments based on customer reviews in IMDB database. Part 2 - Implementing a sequential NLP based text classifier for a social media analytics company using input text parameters to determine the customer sentiments for sarcasm detection
• Face Detection : Recognize, identify and classify faces within images using CNN and image recognition algorithms. In this project, the goal is to build a face recognition system, which includes building a face detector to locate the position of a face in an image and a face identification model to recognize whose face it is by matching it to the existing database of faces.
• Signal Quality Predictor & Image Classifier : Part 1: Deploys a GUI powered by the neural network to build a regressor & classifier respectively for a communications equipment manufacturer. The model predicts the equipment’s signal quality using various parameters from its products, which is responsible for emitting informative signals. Part 2: delivers an image classifier, which can classify numbers from the photographs captured at street level using a Neural Network
• Online retail orders analysis : This project is based on the order management functionality of an online retail store database. Answers to these queries helped the company in making data-driven decisions that impacted the overall growth of the online retail store.
• Supply chain analysis : The project was accomplished by employing supervised learning, ensemble modeling, and unsupervised learning techniques to build and train a prediction model to identify Pass/Fail yield of a particular process entity for a semiconductor manufacturing company. This project helped to determine key factors contributing to yield excursions downstream in the process and enabled an increase in process throughput, decreased time to learn and reduce per-unit production costs.
• Product Identification : Classified a given silhouette as one of three types of vehicle, using a set of features extracted from the silhouette. The vehicle may be viewed from one of many different angles. Segmented cars into various categories by fuel consumption and other attributes.
• Patient data analysis : Predicting the condition of the patient depending on the received test results on biomechanics features of the patients according to their current conditions.
• Customer turnover analysis : Build an AIML model to perform focused marketing by predicting the potential customers who will convert using the historical database.

• Google Data Analytics Certification
• https://www.credly.com/badges/b4de4e9a-b79d-4bf4-bffe-0d0daa547b96/public_url