About
TL;DR: I am M. Tech(Computer Technology) from IIT Delhi. I have an extensive experience of 24+ years in software development in various domains. I have worked for C-DOT, Ciena, HCL, Wipro, Matter and Wadhwani in various capacities.
Tools/Tech:
| Skill | Description/Tool |
|---|---|
| Languages | Javascript/ES6, Typescript, Python, Kotlin, C, C++. |
| Web Related | React, Nextjs, TailwindCSS, NodeJS, ExpressJS, Prisma, Postgresql, MongoDB, Mongoose, GraphQL, REST APIs, Scrapy, Flask, Django, Oauth, GitHub, Jekyll, GitHub-Pages, Bootstrap 4, jQuery, AWS, GCP, Docker, Kubernetes, Heroku, Pythonanywhere. |
| Visualization | D3.js, Matplotlib, Seaborn, Dash (by plotly), Plotly. |
| Python GIS | Geopandas, Shapely, Fiona |
| Machine Learning | Linear Regression, K Nearest Neighbors, Logistic Regression, SVMs, Neural Networks, Decision Trees, Random Forest. K-Means Clustering, PCA, t-SNE, Anomaly Detection, Recommender Systems. |
| Deep Learning | CNNs (LeNet-5, AlexNet, VGG-16, ResNets, Inception, Yolov2, Deepface, FaceNet) RNNs (GRU, LSTM), Transfer Learning. |
| NLP | Bag of Words, TF-IDF, Word embeddings, Glove, Sentiment Analysis, Word2Vec Model, Beam Search, Bleu Score, Attention Models, Trigger word detection. |
| ML Tools/libs | Anaconda-Jupyter, Scikit-Learn, Numpy, Pandas, TensorFlow, Keras, xgboost, Vowpal Wabbit |
| Mathematics | Descriptive Statistics, Inferential Statistics, Probability, Z-Test, Student T-test, Chi-Squared Test, Hypothesis Testing, A/B Testing, Bayesian Analysis. |
Online Certifications/Courses:
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Machine learning course from ODSC: Secured 16th rank among 200 candidates.
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Data Science in Python from Datacamp
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Deep Learning specialization from Coursera