- 🔭 I’m currently working on ...Algorithm Development
- 🌱 I’m currently learning ... Branding and Optimize Programming
- 👯 I’m looking to collaborate on ... YouTube and Open Source Projects
- 🤔 I’m looking for help with ... Data Science
- 👊🤜 I always had a fight with me VS me
- 💬 Ask me about ... Web Development, Data Structures & Algorithms
- 📃 My blogging website ... https://jayambe36.github.io/
- 📃My Portfolio website ... https://jayambe36.github.io/
- 📫 How to reach me: ... [email protected]
▶️ My YouTube channel: ... @DailyCodingWorkout- ⚡ Fun fact: ... I love to Solve Problems. I can do leetcode and gfg problems every day [Workaholic Person]
Note: Top languages is only a metric of the languages my public code consists of and doesn't reflect experience or skill level.
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Here are some of the technologies and tools I work with:
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Programming Languages: Python, HTML5, Tailwind CSS, JavaScript, C++, C, R, SCALA
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Frameworks: Django, Flask, ReactJS, NodeJS, ExpressJS, ReactNative
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Developer Tools: GoogleColab Notebook, VSCode, R-Studio, Jupyter Notebook, Anaconda, Git, Razorpay, Cloudinary, Expo
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Tech Expertise: OOPS, API, Payment Gateway System, Image/Video Upload System, Secure Authentication (jsonwebtoken)
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Databases:
- MongoDB (Hybrid/Cloud - MERN Projects, ML projects with Databases)
- Relational Database - MySQL (Queries, Joins, Trigger, Functions, Stored Procedures)
- DynamoDB
- SQLite (Connecting Python with Databases)
- IBM DB2
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Hosting Platforms: AWS (EC2, ECR, S3, Sagemaker), Render, Vercel, Heroku, PythonAnywhere, 000webhostapp, GoDaddy, Shinnyapp, GitHub Pages
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IBM Tools: IBM Watson, IBM SPSS Modeler, IBM Cloud, IBM Cognos BI, IBM InfoSphere BigInsights, IBM Chatbot, IBM DB2
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Data Science Expertise:
- Predictive Modeling, Statistical Analysis, MLOps, Deep Learning, Data Cleaning, Data Visualization (PowerBI, Tableau)
- Data Mining and Warehousing (Data Cube, OLAP, Multidimensional Data Models)
- Data Transformation, Standardization, Normalization, Handling Missing Data
- Data Lake, JSON Data Format, ETL, Data Pipeline, Data Wrangling, Data Summarization
- Correlation Analysis, Grouping and Aggregating Data, Web Scraping (BeautifulSoup, Scrapy)
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Machine Learning / AI:
- Supervised and Unsupervised Learning, Dimensionality Reduction, Neural Networks (ANN, RNN, CNN), NLP (Natural Language Processing)
- Inferential Statistics, Association Rules, Classification and Prediction (K-means, Decision Tree, Bayesian Classification)
- Clustering (KNN), Exploratory Data Analysis (EDA), ARIMA Models, Model Evaluation/Validation, Hyperparameter Tuning
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Big Data:
- PySpark, Scala, Hive, HBase, Hadoop Ecosystem (HDFS, MapReduce, Yarn, PIG, HIVE, HBASE, Zookeeper)
- Apache Spark, Statistical Analysis (Hypothesis Tests - Z-test, T-test, Chi-square Test)
- Probability and Statistics (Measures of Central Tendency and Dispersion, Random Variables), Linear Algebra, Calculus
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NLP Techniques: Bag of Words (BoW), Word2Vec, Transformers, BERT, Sentiment Analysis
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Libraries / Algorithms:
- A* Algorithm, Scikit-learn (Regression and Classification), Ensemble Methods (Random Forest, Gradient Boosting, XGBoost)
- TensorFlow, Keras (Deep Learning), LSTM (Time Series Prediction, NLP, Speech Recognition)
- NLTK (Text Processing - Classification, Tokenization, Stemming, Tagging, Parsing, Semantic Reasoning)
- Plotly, Matplotlib (Interactive Visualizations - Line Plots, Scatter Plots, Bar Charts, Histograms)
- Seaborn (High-level Interface for Statistical Graphics, Visualization of Univariate/Bivariate Data)
- SciPy (Scientific Computing), Pandas (Data Analysis/Manipulation), NumPy (Numerical Computing)
