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Candidate's Name
EMAIL AVAILABLE PHONE NUMBER AVAILABLE Arlington TX USALinkedIn - Candidate's Name  Machine Learning Engineer at Linear Circuits. & a graduate from the University of Texas at Arlington with an interest in Python, Data Science, Machine learning, Deep learning, neural networks. Actively looking for Software/ Machine Learning Engineer Full Time opportunities starting from Jun Street Address .EDUCATION Master of Science in Computer Science May Street Address
University of Texas at Arlington, Arlington, TX.Relavant Coursework - Machine Learning, neural network, data mining, advanced intelligence system computer vision, design and analysis of algorithms, artificial intelligence, database systems, data analysis and modeling techniques, computer networks. Bachelor of Engineering in Computer Science May 2020 Visvesvaraya Technological University, Belagavi, KA, INDIA . Relevant Coursework - Object oriented programming, Python Application programming, Programming in C and Data Structures, Operating systems, Machine learning, Web Data Management data structures and algorithms.TECHNICAL SKILLSLanguages Python, C, SQL, HTML/CSS JavaScriptML Toolkits NumPy Pandas, Scikit-learn, LangChain, Matplotlib, PyTorch, NLP DL Toolkits Keras, TensorFlow, FastTask, PyTorch, Caffe, MXNet, Neural networks Cloud & Other Tech Azure, GitHub (Git), MongoDB, Tableau, PySpark PROFESSIONAL EXPERIENCE Machine Learning operations Engineer - Linear Circuits Mar 2019-Aug 2021 Implemented end-to-end automated deployment pipelines using Python and SQL, resulting in a substantial 17% reduction in deployment time.Leveraged NLP techniques with tools like NLTK, Spacy, and FastText for sentiment analysis, achieving a 94% accuracy rate. Additionally, incorporated Large Language Models (LLMs) for virtual assistance and advanced NLP tasks.Orchestrated ETL processes using Azure Data Factory for efficient data extraction, transformation, and loading into machine learning workflows. Utilized Azure Databricks, Data Factory, Datalake, DeltaLake, and ADF pipelines to proactively identify and resolve performance issues, ensuring reliable deployment of machine learning models.PROJECTS Naive Bayes Classifier with Text Representation using Bag of Words Jan 2023(Python, Scikit-learn, numpy, pandas)Implemented a Naive Bayes classifier with Bag of Words technique for text representation and classification. Text Classification using fastText (Customizing Own Word Embeddings) Apr 2023(Python, Scikit-learn, fastText, regular expression, pandas) Using fastText library to customize own word embeddings in own domain and then text classification is performed to classify the topics related to ecommerce House Price Prediction using ANN: Jul 2023(Tensorflow, numpy, pandas, Python, matplotlib)Built a multi-linear regression model with Artificial Neural Networks (ANN) to predict house prices Plant Disease Prediction using Conv2D: Aug 2023(Tensorflow, numpy, pandas, Python)With Convolutional neural network through tensorflow a classification model is built, which classifies diseased and normal plants, with an improved accuracy of around 97% and quick results LSTM Model for Stock Prediction: Sep 2023(Tensorflow, numpy, pandas, Python)Utilized RNN and LSTM models for stock prediction, forecasting future price movements based on historical data.