MOHAMMED USMAN MEHBOOB
Flat no. ***, Sai Balaji Enclave Appartment,Yendada, Vishakhapatnam, Andhra Pradesh - 530045
Hardworking graduate with good communication skills along with learning attitude and also has the ability to work with a team and lead one as in when needed. I am seeking for an opportunity to work in a challenging environment where I can prove my technical skills or utilise my fast learning ability to develop new skills when needed for the organization.
X, Narayana Concept School
XII, Narayana Junior College
B.Tech/B.E., GITAM college of Engineering
GITAM UNIVERSITY, 2020
English - Conversational, Hindi - Conversational, Telugu - Conversational HOBBIES
Learning, Fitness, Playing Games
Contest Rating 1507(Percentile 70%) in University of Codesprint,HackerRank,9 September 2018
Tools - MS Word, MS Excel, Eclipse
Data Science with Python
Score - 96/100, Certification Link -
Score - 94/100, Certification Link -
https://www.coursera.org/account/accomplishments/verify/CY7GPKNANB7P Deep learning Specialization
Score - 98/100, Certification Link -
Computer performance prediction
The goal of this project is to predict the CPU performance based on the terms of its cycle time, memory size,etc.
Used various machine learning methods and classified the best method through scores . Hence used random forest regression for this project. Got 98% training accuracy and 94% test accuracy.
Digit recognition system is the working of a machine to train itself or recognizing the digits from different sources like emails, bank cheque, papers, images, etc. and in different real- world scenarios for online handwriting recognition on computer tablets or system, recognize number plates of vehicles, processing bank cheque amounts and so on. Dataset Used : MNIST
Used Jupyter Notebook Open Source Web Application
Accuracy : 99.1%
The Purpose of this project is to find out whether the Mushroom is edible(e) or poisonous(p) based on the different features using the decision tree learning algorithm. Used various machine learning methods and classified the best method through scores . Hence used decision tree algorithm for this project. Got 100 % train and test accuracy .
Diabetes-Prediction-using-Machine-Learning-Algorithms Diabetes is considered as one of the deadliest and chronic diseases which causes an increase in blood sugar.Many complications occur if diabetes remains untreated and unidentified.The motive of this project is to design a model which can prognosticate the likelihood of diabetes in patients with maximum accuracy. Used Jupyter Notebook Open Source Web Application
CLassifiers Used : Logistic Regression,K-neighbours Classifier,Random-Forest Classifier,SVM Classifier,GradientBoostingClassifier,AdaBoostCLassifier Facial recognition is a category of biometric software that maps an individual's facial features mathematically and stores the data as a faceprint. The software uses deep learning algorithms to compare a live capture or digital image to the stored faceprint in order to verify an individual's identity.
Web Scrapping using BeautifulSoup and Selenium
Arcface Loss function
Resnet 50 architecture
Programming Language used: Python
Working on Deployment using Flask