Freelancer logo How It Works Browse Jobs Log In Sign Up Post a Project Profile cover photoundefined
You're now following .
Error following user.
This user does not allow users to follow them.
You are already following this user.
Your membership plan only allows 0 follows. Upgrade here.
Successfully unfollowed user.
Error unfollowing user.
You have successfully recommended
Error recommending user.
Something went wrong. Please refresh the page and try again.
Email successfully verified.
User Avatar
$25 USD / hour
Flag of PAKISTAN
lahore, pakistan
$25 USD / hour
It's currently 1:50 PM here
Joined August 8, 2008
0 Recommendations

Dr. Muhammad Nadeem M.

@nadeemajeedch

5.0 (1 review)
0.0
0.0
$25 USD / hour
Flag of PAKISTAN
lahore, pakistan
$25 USD / hour
100%
Jobs Completed
100%
On Budget
100%
On Time
N/A
Repeat Hire Rate

Project Manager / Data Scientist

22 Years of Experience in Computer science and 4+ years as a Data Scientist, broad-based experience in building data-intensive applications, and overcoming complex architectural and scalability issues in diverse industries. Having expertise in data storage structures, data mining, and data cleansing. Translating numbers and facts to inform strategic business decisions. Analyzing sales figures, market research, logistics, or transport data. Creating and following processes to keep data confidential. Coming up with solutions to costly business problems.
Freelancer Python Developers Pakistan

Contact Dr. Muhammad Nadeem M. about your job

Log in to discuss any details over chat.

Portfolio Items

The use of mobile apps is increasing rapidly. These apps have thousands of reviews which are widely acknowledged as a valuable resource for the community involved in the development of mobile apps. In this study, we contend that these reviews can be used to generate software change request documents for improving mobile apps. A pre-requisite for generating such a document is the identification of Software Change Requests (SCR) from the user reviews.
we have scrapped review of seven Mobile Apps and developed a dataset that can be used for training of machine learning techniques for the automatic identification of SCRs.We have documented the annotation guidelines that are used to distinguish between SCR and non-SCR sentences. These guidelines can be used to enhance the developed dataset, as well as to develop new datasets. As another contribution, we have evaluated the effectiveness of five supervised learning techniques for their ability to identify sentences from user reviews.
Extracting Software Change Requests from Mobile App Reviews
Extracting Software Change Requests from Mobile App Reviews
An Efficient SMOTE-Based Deep Learning Model for Heart Attack Prediction:
Cardiac disease treatments are often subjected to the acquisition and analysis of a vast quantity of digital cardiac data. These data can be utilized for various beneficial purposes. The proposed research work presents a cost-effective solution to predict heart attack with high accuracy and reliability by using uses a synthetic minority oversampling technique (SMOTE) to handle given imbalance data.
Efficient SMOTE-Based DL Model for Heart Attack Prediction
Alzheimer's disease (AD) is the most common form of dementia, which results in memory-related issues in subjects. An accurate detection and classification of AD alongside its prodromal stage i.e., mild cognitive impairment (MCI) is of great clinical importance. In this paper, an Alzheimer detection and classification algorithm is presented. The bag of visual word approach is used to improve the effectiveness of texture based features, such as gray level co-occurrence matrix (GLCM), scale invariant feature transform, local binary pattern and histogram of gradient. The importance of clinical data provided alongside the imaging data is highlighted by incorporating clinical features with texture based features to generate a hybrid feature vector. The features are extracted from whole as well as segmented regions of magnetic resonance (MR) brain images representing grey matter, white matter and cerebrospinal fluid.
https://www.sciencedirect.com/science/article/pii/S1746809418300508
Multi-class Alzheimer's disease classification
Ensemble-classifiers-assisted detection of cerebral microbleeds in brain MRI
Cerebral Microbleeds (CMBs) are considered an essential indicator in the diagnosis of critical cerebrovascular diseases such as ischemic stroke and dementia. The framework consists of three phases: brain extraction, extraction of initial candidates based on threshold and size-based filtering, and feature extraction and classification of CMBs from other healthy tissues in order to remove false positives using Support Vector Machine, Quadratic Discriminant Analysis, and ensemble classifiers.
Detection of cerebral microbleeds in brain MRI
Computer-assisted language learning (CALL) systems provide an automated framework to identify mispronunciation and give useful feedback. this research investigates the use of the deep convolutional neural network for mispronunciation detection of Arabic phonemes. This model uses convolutional neural network features (CNN_Features)-based technique and a transfer learning-based technique to detect mispronunciation detection.
Mispronunciation detection using Deep Learning
Mispronunciation detection using Deep Learning
Mobile Application Development Center Logo
Mobile Application Development Center Logo

Reviews

Changes saved
Showing 1 - 1 out of 1 reviews
Filter reviews by: 5.0
$10.00 USD
Very helpful.
PHP
User Avatar
Flag of Mark A. @bioxsl
11 years ago

Experience

Associate Professor / Data Scientist

Data Science Department, University of the Punjab, Lahore
Sep 2019 - Present
Research / Teaching Post Graduate Students, working on multiple projects of Data Science. Consultancy as Data Scientist to multiple companies. Managing multiple projects as Project Manager.

Education

PhD Computer Engineering

University of Engineering and Technology, Taxila, Pakistan 2010 - 2015
(5 years)

Qualifications

Project Management Professional (PMP)®

Project Management Institute
2020
The PMP is the gold standard of project management certification. Recognized and demanded by organizations worldwide, the PMP validates your competence to perform in the role of a project manager, leading and directing projects and teams.

Lean Six Sigma Green Belt

Global Institute
2021
Lean Six Sigma Green Belt is a professional who is well versed in the core to advanced elements of Lean Six Sigma Methodology, who leads improvement projects and serves as a part of more complex improvement projects

PRINCE2® Agile

AXELOS
2021
PRINCE2 Agile Practitioner takes the knowledge acquired at the Foundation level and applies it to the workplace, using real-world management examples.

Publications

An Efficient SMOTE-Based Deep Learning Model for Heart Attack Prediction

https://www.hindawi.com/journals/sp/2021/6621622/
Cardiac disease treatments are often subjected to the acquisition and analysis of a vast quantity of digital cardiac data. These data can be utilized for various beneficial purposes. The proposed research work presents a cost-effective solution to predict heart attack with high accuracy and reliability by using uses a synthetic minority oversampling technique (SMOTE) to handle given imbalance data.

Extracting Software Change Requests from Mobile App Reviews

https://ieeexplore.ieee.org/iel7/9680270/9679822/09680294.pdf
The mobile apps have thousands of reviews which are widely acknowledged as a valuable resource for the community involved in the development of mobile apps. We contend that these reviews can be used to generate software change request documents for improving mobile apps. A pre-requisite for generating such a document is the identification of Software Change Requests (SCR) from the user reviews. Manual processing of this large number of reviews to identify SCRs is a resource-intensive task....

Blind Image Deblurring Using Laplacian of Gaussian (LoG) Based Image Prior

International Journal of Innovations in Science & Technology
It is possible to deconvolve a blurred image into its original form without any knowledge of the actual image or the process that leads it to be blurred, known as a point spread function. Two phases are involved in producing a blurred image: convolution and deconvolution of the PSF from the blurred image. Video conferencing, diagnostic imaging, and celestial imaging all require this blind deconvolution, but it is difficult to calculate the PSF before the operation.

Ensemble-classifiers-assisted detection of cerebral microbleeds in brain MRI

https://www.sciencedirect.com/science/article/pii/S0045790617332767
Cerebral Microbleeds (CMBs) are considered an essential indicator in the diagnosis of critical cerebrovascular diseases such as ischemic stroke and dementia. The framework consists of three phases: brain extraction, extraction of initial candidates based on threshold and size-based filtering, and feature extraction and classification of CMBs from other healthy tissues in order to remove false positives using Support Vector Machine, Quadratic Discriminant Analysis and ensemble classifiers.

Mispronunciation detection using deep convolutional neural network and transfer learning-based model

https://ieeexplore.ieee.org/iel7/6287639/8600701/08695703.pdf
Computer-assisted language learning (CALL) systems provide an automated framework to identify mispronunciation and give useful feedback. this research investigates the use of the deep convolutional neural network for mispronunciation detection of Arabic phonemes. This model uses convolutional neural network features (CNN_Features)-based technique and a transfer learning-based technique to detect mispronunciation detection.

An adaptive doctor-recommender system

https://www.tandfonline.com/doi/pdf/10.1080/0144929X.2019.1625441
A hybrid doctor-recommender system is proposed, by combining different recommendation approaches; content base, collaborative and demographic filtering to effectively tackle the issue of doctor recommendation. The proposed system addresses the issue of personalization by analyzing a patient's interest in selecting a doctor. It uses a novel adaptive algorithm to construct a doctor's ranking function.

Multi-class Alzheimer's disease classification using image and clinical features

https://www.sciencedirect.com/science/article/pii/S1746809418300508
Cardiac disease treatments are often subjected to the acquisition and analysis of a vast quantity of digital cardiac data. These data’s utilization becomes more important when dealing with critical diseases like a heart attack where patient life is often at stake. The research work presents a cost-effective solution to predict heart attacks with high accuracy and reliability by predicting heart attack via various machine learning algorithms without the involvement of any feature engineering.

Contact Dr. Muhammad Nadeem M. about your job

Log in to discuss any details over chat.

Verifications

Preferred Freelancer
Identity Verified
Payment Verified
Phone Verified
Email Verified
Facebook Connected

Certifications

vworker.png Foundation vWorker Member

Top Skills

Python Website Design Data Processing Excel WordPress

Browse Similar Freelancers

Python Developers in Pakistan
Python Developers
Website Designers
Data Processing Executives

Browse Similar Showcases

Python
Website Design
Data Processing
Excel
Previous User
Next User
Invite sent successfully!
Registered Users Total Jobs Posted
Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)
Copyright © 2023 Freelancer Technology Pty Limited (ACN 142 189 759)
Loading preview
Permission granted for Geolocation.
Your login session has expired and you have been logged out. Please log in again.