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$20 USD / hour
Flag of EGYPT
cairo, egypt
$20 USD / hour
It's currently 5:55 PM here
Joined September 30, 2020
0 Recommendations

Ahmed Mahmoud M.

@ahmedtryaq

 5.0 (5 reviews)
4.0
4.0
100%
100%
$20 USD / hour
Flag of EGYPT
cairo, egypt
$20 USD / hour
100%
Jobs Completed
69%
On Budget
100%
On Time
33%
Repeat Hire Rate

Data Scientist | Machine Learning Engineer

I worked on many projects performing business intelligence tasks including visuals and reports, data wrangling, descriptive & inferential statistics, a/b testing, supervised machine learning, clustering analysis and deep learning. I thank Allah for getting 5-star ratings from all clients I worked with so far. And I'm aspirating to build a great network of the best professional colleagues and clients. Outside of work, I love gaining interdisciplinary knowledge by reading continuously in multiple fields. ✔️ My top Skills: - Data Analysis (SQL, Python, Pandas, Numpy, Tableau, Alteryx) - Data Visualization (Matplotlib, Seaborn) - Machine Learning (Sklearn) - Deep Learning (TensorFlow) - NLP (Transformers, HuggingFace, Spacy, NLTK) - Big Data Analysis (PySpark) - Statistics & Hypothesis testing (StatsModels)
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Portfolio

9046116
Performed principle component analysis and clustering of customers data to predict potential customers. Tools used: Pandas, Numpy, Matplotlib, Seaborn, Sklearn (Python).
Customers clustering using sklearn.
9046096
Spam detection model using NB algorithm, done in SciKit Learn, Pandas, Numpy (Python).
NLP - Document classification
8475561
To view full project and report on Github: https://github.com/atryaq/Different-ab-testing-approaches
A/b testing & logistic regression project on Github.
8475502
Scraping links of google search results of specific keywords in python without API. Packages used: BeautifulSoup urllib Pandas Numpy time To view the full code please visit my Github profile: @atryaq.
Scrapping google search results.
8475495
Scrapped a list of all Spanish companies names and website links from companiess.com [9979 rows].
Scraping spanish companies list from companiess.com
7438000
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)
9046116
Performed principle component analysis and clustering of customers data to predict potential customers. Tools used: Pandas, Numpy, Matplotlib, Seaborn, Sklearn (Python).
Customers clustering using sklearn.
9046096
Spam detection model using NB algorithm, done in SciKit Learn, Pandas, Numpy (Python).
NLP - Document classification
8475561
To view full project and report on Github: https://github.com/atryaq/Different-ab-testing-approaches
A/b testing & logistic regression project on Github.
8475502
Scraping links of google search results of specific keywords in python without API. Packages used: BeautifulSoup urllib Pandas Numpy time To view the full code please visit my Github profile: @atryaq.
Scrapping google search results.
8475495
Scrapped a list of all Spanish companies names and website links from companiess.com [9979 rows].
Scraping spanish companies list from companiess.com
7438000
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)
Dataset This data set includes details about individual rides made in a bike-sharing system covering the greater San Francisco Bay area during the period from April to June (spring 2020). Summary of Findings Most of customers were casual customers, and most of bikes rided were electric bikes. Casual customers who used docked bikes have the heighst chances for having a very long trip. While members who used electric bikes are related with the least trip duration. Number of trips each week increases over time. Visually, there is a potential negative correlation between number of rides per week and mean ride duration, however, further analysis is required for assessing this relationship. To watch the final visualization slide show: download and open 'slides.slides.html' file. For more extensive details, you can check 'exploration.ipynb' notebook. Key Insights for Presentation Proportion of users in each category. Proportion of bike types. Effect of user/bike categoty on trip duration.
Exploring Ford GoBike System Data (spring 2020)

Reviews

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Showing 1 - 5 out of 5 reviews
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5.0
$150.00 USD
MRI Angle Measurement Inter-rater Reliability
Excellent work. Efficient and extremely thorough.
Research
Statistics
Medical
Statistical Analysis
L
Flag of David L.
@levid41
•
2 years ago
5.0
$260.00 AUD
ML Project for Ahmed Mahmoud M.
Have been working with Ahmed for quite some time now. He has delivered all projects as per the requirements. Makes sure all doubts are cleared before the start of the project and delivers great work. Expert with python and machine learning algorithms and applies logic to the work which has been really helpful. Always available for changes at a later stage. Will surely keep working with him.
Python
Web Scraping
Machine Learning (ML)
Data Mining
+1 more
User Avatar
Flag of Hass S.
@hasscvinc
•
3 years ago
5.0
£120.00 GBP
I need a python developer with experience of tkinter and matplotlib
A pleasure to work with. He fixed all the problems in my app, displaying live data graphically. I would definitely recommend
Python
Software Architecture
H
Flag of Richard H.
@hatfieldr
•
3 years ago
5.0
£15.00 GBP
Project for Ahmed Mahmoud M.
Second time using Ahmed Mahmoud and once again did a great job of solving my coding problem.
Python
Excel
SQL
Web Scraping
Statistics
+1 more
M
Flag of Marcus H.
@Morph10
•
3 years ago
5.0
£50.00 GBP
Help with my statistics program/website - coding and troubleshooting
Ahmed Mahmoud did a great job troubleshooting my problem and also did a great job of cleaning my code up. Always very quick to respond and was very polite. I took a gamble using someone new with no previous feedback, but was well worth it. Would recommend.
Python
Web Scraping
Software Architecture
HTML
M
Flag of Marcus H.
@Morph10
•
3 years ago

Experience

Data Scientist

Freelance
Apr 2021 - Present
I worked on many projects performing business intelligence tasks including visuals and reports, data wrangling, descriptive & inferential statistics, a/b testing, supervised machine learning, clustering analysis and deep learning.

Data Analyst

Freelance
Jul 2018 - Apr 2021 (2 years, 9 months)
Worked on miscellaneous data related tasks including: - Web scrapping & data extraction - Data integration from different sources - Data wrangling - Data Analysis - Reporting and visualization

Education

Bechelor

Ain Shams University, Egypt 2017 - 2021
(4 years)

Qualifications

Intro to Machine Learning with Tensorflow Nanodegree

Udacity
2021
Learned foundational machine learning algorithms in detail, starting with data cleaning and supervised models. Then, moved on to exploring deep and unsupervised learning.

Advanced Data Analysis Nanodegree

Udacity
2020
- Learned the whole data analysis process of questioning, wrangling, exploring, analyzing, and communicating results. - How to work with data in Python using libraries like NumPy and Pandas. - Applying inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models. - Applying sound design and data visualization principles to the data analysis process.

Data Analysis Track

Udacity
2019
­

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Certifications

preferredfreelancer-1.png Preferred Freelancer Program SLA 1 82%

Top Skills

Python 7
Web Scraping 5
Data Mining 4
Data Science 4
Statistics 2

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