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$20 USD / hour
Flag of PKFlag of PK
wah cantt,
pakistan
$20 USD / hour
It's currently 2:41 AM here
Joined September 15, 2017
0 Recommendations

Muhammad Abdur Rehman K.

@abdurrehman1985

monthly-level-three.svg
4.7 (5 reviews)
4.7 (5 reviews)
3.4
3.4
$20 USD / hour
Flag of PKFlag of PK
wah cantt,
pakistan
$20 USD / hour
100%
Jobs Completed
100%
On Budget
100%
On Time
14%
Repeat Hire Rate

Engineer & Junior Data Scientist

Developed my expertise in machine learning by completing core specializations in Data Science. Analyzed different industries dataset for designing algorithms related to predictive modeling and clustering but not limited to automotive, banking, education, energy, housing, medical, social networks (Twitter), retail, telecom, and trading. Python programming is an essential part of my work with datasets; in any format like CSV, Excel, JSON, or XML on the Kaggle Cloud platform (mostly, but some work is done on GCP too). The libraries I mostly use are Pandas, NumPy, Seaborn, Keras, OpenCV, Pytesseract, and PIL. Extensively worked on Data Mining techniques for improving the algorithms related to supervised learning or unsupervised learning like clustering and dimensionality reduction (The PCA technique). Experienced in designing the algorithms with SVM, Decision Trees, Logistic Regression, Ensemble methods, and modern machine learning algorithms like Hybrid and Stacked Generalization and Deep Learning algorithms. In some projects during certifications, SQL is widely utilized.
Freelancer
Python Developers
Pakistan

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Portfolio Items

Ranked 508 (from 4245) in Jane Street Market Prediction, a competition to run the model against the future real market data. A classification problem handled through by omitting volatility days (outliers) and model training through Light GBM algorithm.
Jane Street Market Transaction Data
Artificial Intelligence is like electricity. It has transformed many industries. Today we can predict the prices of any property given the previous information. Everything evolves with the passage of time. In fact, AI is also evolving with improved algorithms like ensembles, hybrid, and stacked ones. With the advancement of these algorithms, we can now acquire better results.  
The research regarding estimating London Housing prices is based on UK transaction price paid data with adding some colors like integrating macroeconomic indicators (GDP, inflation, Employment and Unemployment, and Consumer Price Index),subways (within 0.5,1.0 & 2.0 miles property radius), bus stops (within 0.5 miles property radius) and supermarkets or retail stores (within 0.5,1.0 & 2.0 miles property radius). 

After applying Data Analysis, only transaction and macroeconomic data are viable for modeling.
Estimating London Residential Prices
Artificial Intelligence is like electricity. It has transformed many industries. Today we can predict the prices of any property given the previous information. Everything evolves with the passage of time. In fact, AI is also evolving with improved algorithms like ensembles, hybrid, and stacked ones. With the advancement of these algorithms, we can now acquire better results.  
The research regarding estimating London Housing prices is based on UK transaction price paid data with adding some colors like integrating macroeconomic indicators (GDP, inflation, Employment and Unemployment, and Consumer Price Index),subways (within 0.5,1.0 & 2.0 miles property radius), bus stops (within 0.5 miles property radius) and supermarkets or retail stores (within 0.5,1.0 & 2.0 miles property radius). 

After applying Data Analysis, only transaction and macroeconomic data are viable for modeling.
Estimating London Residential Prices
Artificial Intelligence is like electricity. It has transformed many industries. Today we can predict the prices of any property given the previous information. Everything evolves with the passage of time. In fact, AI is also evolving with improved algorithms like ensembles, hybrid, and stacked ones. With the advancement of these algorithms, we can now acquire better results.  
The research regarding estimating London Housing prices is based on UK transaction price paid data with adding some colors like integrating macroeconomic indicators (GDP, inflation, Employment and Unemployment, and Consumer Price Index),subways (within 0.5,1.0 & 2.0 miles property radius), bus stops (within 0.5 miles property radius) and supermarkets or retail stores (within 0.5,1.0 & 2.0 miles property radius). 

After applying Data Analysis, only transaction and macroeconomic data are viable for modeling.
Estimating London Residential Prices
Artificial Intelligence is like electricity. It has transformed many industries. Today we can predict the prices of any property given the previous information. Everything evolves with the passage of time. In fact, AI is also evolving with improved algorithms like ensembles, hybrid, and stacked ones. With the advancement of these algorithms, we can now acquire better results.  
The research regarding estimating London Housing prices is based on UK transaction price paid data with adding some colors like integrating macroeconomic indicators (GDP, inflation, Employment and Unemployment, and Consumer Price Index),subways (within 0.5,1.0 & 2.0 miles property radius), bus stops (within 0.5 miles property radius) and supermarkets or retail stores (within 0.5,1.0 & 2.0 miles property radius). 

After applying Data Analysis, only transaction and macroeconomic data are viable for modeling.
Estimating London Residential Prices
Objective
We have to analyze the incidents and predict the accident risk involve at those locations where the accident and non-accident incident were happened together at different times on the same location in the past.

Observation & Recommendation
We observed that there are many places where multiple incidents happened. It means there are chances of accident risk is involved. Like traffic jam in hazardous areas, where plenty of chances of a minor accident can happen there. We didn't consider the time where an incident has happened. The time factor may also be a good feature to analyze further. It could give us a better probability.

Conclusion
The accuracy of the model is above 90% percent. It means the model fits well. We can concentrate on those commonplaces which are sharing the common coordinates. It will help us to minimize accident risks.
Accident Risk Places Prediction
Sentiment Classifier
Through Python programming, created Sentiment Classifier that calculates the net score on the basis of positive and negative words in tweets using text and CSV files. Besides, mashed up two APIs to create a movie recommender.
Sentiment Classifier
Tableau Story Telling
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards
The attached images are my current work related to Meaningful Data Visualization on Tableau. More will come soon.
Tableau Dashboards

Reviews

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Showing 1 - 4 out of 4 reviews
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5.0
$50.00 CAD
10/10 recommend! delivered project on time
Python
Algorithm
A
Flag of CA Anany S. @anony2022
11 days ago
4.8
$175.00 USD
The freelancer is awesome.
M
Flag of SA Rana A. @moments3
2 years ago
4.6
£200.00 GBP
Mohammad is an excellent professional. He took ownership and provided brilliant ideas. I’ll definitely be open to hire him again for Machine Learning projects
A
Flag of GB Ade A. @AdeAwonaike
2 years ago
5.0
₹3,000.00 INR
Muhammad is very meticulous freelancer and he has good expertise in his areas very prompt in responding would love to work with him again in future projects [09 December, 2019] Muhammad Abdur is very responsive and charging reasonable pay he is working meticulously and customer oriented
Python
Web Scraping
Software Architecture
Machine Learning (ML)
Data Mining
User Avatar
Flag of IN Sahaana P. @Sahaana74
2 years ago

Experience

Freelance

Self Employed
Aug 2018 - Present
• Giving machine-learning solutions to different industries customers. • Analyzed different industries dataset for designing algorithms related to predictive modeling and clustering but not limited to automotive, banking, education, energy, housing, medical, and telecom. • Participating in Kaggle Competitions regularly to enhance skills in Data Analysis and algorithms.

Sr Sales Engineer

Orient Energy Systems
Feb 2015 - Jun 2016 (1 year, 4 months)
• Generated yearly profit of 18% on overall rental sales of high rating diesel and gas gensets of renown brands, Caterpillar, Cummins, and Jenbacher, up to 4MW – reported to Sales Manager. • Achieved division goals of 4% annual growth by meeting sales objectives, forecasting and securing product sales. • Reduced client overall expenses on electricity by up to 2 rupees per unit on providing gas genset solutions.

Sales Engineer

Usama Distributors
Apr 2013 - Jan 2015 (1 year, 9 months)
• Increased sales by 37% in the territory through distribution management of lubricant and FMCG products. • Reduced 15% distributor house expenses over effective micro sales management.

Education

BE

Air University, Pakistan 2004 - 2008
(4 years)

Qualifications

Certifications

Coursera
2021
Deep Learning AI

Certifications

Coursera
2020
Statistics with Python

Certifications

Coursera
2020
Python Programming 3

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Top Skills

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