Mohammed Zeeshan Mulla's Projects
find the chance of admission of a candidate based on his/her GRE Score (out of 340), TOEFL Score (out of 120), rating of the University (out of 5) in which he/she is trying to get admission, Strength of the SOP (out of 5), strength of the Letter Of Recommendation (out of 5), CGPA (out of 10) and the research experience (0 or 1) deployed on GCP
A Project on prediction of Air Quality index from Data Collection, Data Pre-processing and applying Machine Learning Algorithms- Linear, Ridge and Lasso, Decision Tree, Random Forest, KNN, XGBoost...... AND applied TPOT just to see it work. *_*
A python library to scrape data from amazon.com
A topic-centric list of HQ open datasets.
AQI model deployed on AZURE cloud
VGG on Cat Dog dataset using Transfer Learning.
Dictionary Chatbot on Slack using Amazon LEX, Amazon Lambda , Oxford Dictionary api
Numpy, Pandas, Matplotlib, Seaborn, Plotly and Cufflinks
Docker implementation with Hyper-V enabled pc, further will make use of Kubernetes which is container orchestration system for Docker containers & with Docker Swarm
The open-source repo for docs.github.com
demo
EDA on Titanic, Feature Selection Techniques on titanic dataset AND MANY MORE, Univariate, Bivariate, Multivariate analysis
Deployment of ML model using Heroku Platform As A Service
An unofficial Kaggle datasets downloader
login and register form with css html php
ML Algorithms notebook with dataset. Will keep on Updating this Repo.
Machine translation to convert human readable dates to machine readable dates. (MT) refers to fully automated software that can translate source content into target content of different type. Neural Machine Translation is method which utilizes neural networks to achieve this task.
A repo for all the relevant code notebooks and datasets used in my Machine Learning tutorial videos on YouTube
Locking Unlocking system for mobile remote plan
Tokenization, Stemming, Lemmatization, Bag of words, TF-IDF
Question answering (QA) system aims at retrieving precise information from a large collection of documents against a query. The proposed architecture defines four basic modules suitable for enhancing current QA capabilities with the ability of processing complex questions. The first module was the question processing, which analyses and classifies the question and also reformulates the user query. The second module allows the process of retrieving the relevant ontological relations from the given question. The next module processes the retrieved words from question. Natural language processing techniques are used for processing the question and documents and also for answer extraction. Ontology and domain knowledge are used for reformulating queries and identifying the relations.
Streaming video of pedestrians movement using Opencv and microframework-flask
Datatypes, MySQLConnection, Pybasics, Operators, Statements, lambda, file handling, Exception, Multithreading, dateandtime, functools, Anova with numpy
R Markdown Kernel [](https://github.com/rstudio/rmarkdown/issues)
project from web scrapping an ecommerce website product reviews (user required) till deployment of the model to local machine can be stored using MongoDb And deployment of same on cloud platform like Heroku, Azure.
Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier).
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