Hello, Nice to see you. I am Vedant Dave, a detailed oriented, visionary data science graduate currently doing freelancing at UpWork. I love analyzing practical problems and discovering their solutions using machine learning. I have a deep interest in AI and want to work with machine learning applications research, development and operations. I have a nano degree in “Deep Learning Engineer” and also have a master’s degree in data science. I’d love to combine my previous work experience in data analytics, Machine learning and engineering with “the state of technology” to continue solving practical world problems for improving business & human values.
I have working experience in data analytics & reporting, ML/DL model developing tasks and database management. I also worked on a special project of computer vision “tablet crack detection for pharma” which includes model development, accuracy improvement and model deployment using cloud technology with proper production environment including CI/CD pipeline and microservices.
I also worked on more than 10+ projects related to banking, business intelligence, marketing and energy datasets. Currently, I am also working on a Kaggle competition “HubMAP: Hacking the Kidney”,a research-based project on my self-interest. I also like to read research papers and ambitious to convert them into code.
My Area of Interest
Have experience of paper implementation with PyTorch Keras - Tensorflow. (RNN/RNN/GAN)
Knowledge of Modern ML algorithms, implementation with scikitlearn, NLTK. Know Pandas, Matplotlib & Numpy.
Experience of Production Workflow with CI/CD pipeline, RESTfulAPI and Flask framework.
Worked with AWS (EC2, sagemaker, lambda, EMR, elasticbean & APIs. familiar with AZURE & GCP.
Worked on customer, sales, production & Machine data. Have extended knowledge of python, Tableau & Qlik.
Have Experience with scaled service architecture, App. dockerization & Kubernetes (EKS, GKS) .
Have project experience with spark(scala), Hadoop ecosystem, MapReduce Job and Hive Analytics
Won Bertelsmann Scholarship and successfully completed the Udacity course work related to Deep learning model architectures (CNN, RNN, GAN/DCGAN).
Develop high accuracy projects such as Dog Breed Classifications, Fake TV Script Generation, Celebrity Face Generation and AWS deployment of Sentiment Prediction Application.
Gained and apply new skills related to data science via projects, paper discussion and presentations throughout the academic year. Major Course Work :
Gained knowledge of Electrical and Electronic technology, power system management, its distribution, Energy data analytics, Micro processor, Microcontroller and networking intrumentations. Worked on "Solar Power cell efficiency improvement" and "GPS based speed control of Electric Motor using PWM wave" projects as a part of internship.
Machine Learning / Cloud / Microservices
Self Learning Courses and Certifications
Currently, I am looking for freelancing work on UpWork in the field of Data Science. I am a newbie in freelancing, but my professional experience and hands-on expertise give me confidence for work accomplishment.
Worked with the Data Science team to generate python logic functions, efficient SQL queries for improving business operations. Performed daily responsibilities of row data gathering, cleaning, analytics & visualization, Tableau/BI dashboard reporting. Worked on Machine Learning, Computer vision, and big data technology assignments for improving the decision score matrix. Handled Adhoc responsibility of QA data quality, integrity, and gap analytic tasks.
Served as project management team member responsible for project requirements, business needs, process alternation, and cost estimation. Worked on SCM system database creation, data cleaning, preprocessing, integration tasks. Handled material tracking system designing, project progress analysis reports, and dashboard creation.
"When you’ve written the same code 3 times, write a function,
When you’ve given the same in-person advice 3 times, write a blog post"
- David Robinson
Blog about Sentiment Analysis, differnet analytic approaches, Neural Network Approach in depth and Text Feature Extraction.
Explaination of Google Colab Code for data preprocessing, Network Architecure, Training & Testing Logic, Learning Rate adjustment.
Applied Hypothesis testing for Noisy data elimination, complexity reduction and polarity cutoff and ML Model Improvment