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Akinwande K - keras developerLD Talent logo

Akinwande K

The star rating is a representation of the overall rating, calculated as the mean of the client satisfaction rating, the average client interview rating, and internal interview scores.

The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.

If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
Software Engineer Preferred Title
$43.75 /hr $ 28.0K /yr Hourly Rate and Yearly Salary
Overview Experiences LD Experiences Qualifications
Overview
Basic Summary
LD Talent History
  • Worksession Approval 64.0%
  • Average Response Time 6.1 hours
  • Average Count of Messages/Day 0.9
  • Project Completion Rate 2/4
  • Interview Acceptance Rate 4/6
  • Timezone Overlap 44h PST, 49h UTC
  • Earned Hours 3.50
Talent's Devices
  • Desktop Mac
  • Phone iPhone
General
  • Member Since Jan 27, 2020
  • Profile Last Updated Nov 14, 2021
  • Last Activity March 24, 2022, 6:52 p.m. UTC
  • Location Nigeria
Profile Summary
Adaptable Data Scientist skilled in recording, interpreting and analysing data in a fast-paced environment. Able to play a key role in analysing problems and coming up with creative solutions as well as producing methodologies and files for effective data management. A quick learner who can absorb new ideas and can communicate clearly and effectively.
Skills
Total Experience: 6+ years
  • keras (2E, 6Y)

    2 experiences, across 6 years
  • Python (4E, 6Y, 1C)

    4 experiences, across 6 years, with 1 course
  • Deep learning (6Y)

    6 years of experience
  • Machine learning (4E, 6Y, 1C)

    4 experiences, across 6 years, with 1 course
  • AWS S3 (6Y)

    6 years of experience
  • Web scrapers (5Y)

    5 years of experience
  • Natural language processing (5Y, 1C)

    5 years of experience, with 1 course
  • Python Selenium (5Y)

    5 years of experience
  • scikit-learn (2E, 2Y)

    2 experiences, across 2 years
  • Data Science

  • Docker

  • Power BI

  • Tableau

  • Microsoft Excel

  • Data Analytics

  • MySQL

  • Apache Spark (1C)

    1 course
  • AWS ElasticMapReduce (1C)

    1 course
  • AWS ECR (1C)

    1 course
  • Data Engineering (1C)

    1 course
  • Twitter APIs (1C)

    1 course
  • Google NLP API (1C)

    1 course
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 44h PST, 49h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
10 - 20
13 - 19
13 - 19
13 - 19
13 - 19
14 - 20
11 - 20
PST
03 - 13
06 - 12
06 - 12
06 - 12
06 - 12
07 - 13
04 - 13
Experience
Software Engineer
Contract
Jul 2019 - Present
Terragon group Company
Media and Communication Industry
Project: Building click through rate models
  • keras
  • Machine learning
  • Deep learning
  • AWS S3
  • Python
  • Carried out the extract, load and transform process on the data from AWS S3 with python scripts.
  • Deployed machine learning models into production as a RESTful web service.
  • Conducted cluster analysis to generate segmented profiles for customers using deep learning
  • Developed a wide and deep neural network using the Keras API to predict whether a mobile ad will be clicked or not.
Github Links
  • https://github.com/Sensei-akin/slik_python_package/
Software Engineer
Passion Project
May 2020 - Present
Tekspace Company
Technology Industry
Project: web scraping
  • Natural language processing
  • Machine learning
  • Python Selenium
  • Web scrapers
  • Python
  • Built web scrapers from scrapsfromthelofts.com with the BeautifulSoup package.
  • I used python selenium for creating the headless browser and debugged the web scraping script.
  • Used machine learning algorithms to predict sentiment of different comedians.
  • Used Natural language processing to build a sentiment analysis model.
Software Engineer
Contract
Jun 2020 - Sep 2020
Ensemble lab Company
Finance Industry
Project: Building Credit risk models
  • Machine learning
  • Data Science
  • Docker
  • scikit-learn
  • Python
  • I developed a loan default model using scikit-learn API to predict if a person will default on a loan.
  • Dockerized my model in order for the API to be consumed in production.
  • Used my data science and analytical skills to effectively carry out my job.
  • Carried out the extract, load and transform process on the data from AWS S3 with python scripts.
  • Developed machine learning algorithm to predict how much a loanee earns per month based on some variables.
Software Developer
Contract
Jun 2019 - Aug 2019
Terragon group Company
Arts and Entertainment Industry
Project: Data Analyst
  • Data Analytics
  • Power BI
  • Microsoft Excel
  • Tableau
  • MySQL
  • Daily analysis and reporting across all live campaigns using my data analytics skills.
  • Proficient use of Microsoft Excel to seamlessly perform my duties.
  • Data gathering for marketing campaigns using MySQL.
  • Created a marketing dashboard with Tableau.
  • Plotted graphs and charts with Power BI for easy reporting and visualisation of campaign performance.
LD Experience
Client Projects
Developer
Contract
Sep 2021 - Oct 2021
Adava Client's Company/Project
  • Machine learning
  • Python
  • scikit-learn
  • keras
    Video Projects
    How to implement django-tenant-schemas with a fixed URL
    Sep 2020 - Jan 2022
    Frontend Developer
    Technology
    • keras
    • Python
    • Deep learning
    • Machine learning
    • AWS S3
    • Web scrapers
    • Natural language processing
    • Led user research for a new construction site documentation tool.
    • Hosted workshops to synthesize user insights into design requirements.
    • Designed 3D concepts and built prototypes to investigate new tool form factors.
    • Researched existing digital solutions and prioritized key features for app release.
    Website Links
    • https://blog.learningdollars.com/2020/08/02/how-to-implement-django-tenant-schemas-with-a-fixed-url/
    • https://agile-headland-01373.herokuapp.com/
    Github Links
    • https://github.com/MainaKamau92/rickandmortycharacters
    • https://github.com/learningdollars/mainak-django-tenant-schemas
    LD Ventures
    Thea
    Sep 2020 - Jan 2022
    Frontend Developer
    Technology
    • keras
    • Python
    • Deep learning
    • Machine learning
    • AWS S3
    • Web scrapers
    • Natural language processing
    • I used the Django Rest Framework to create a multi tenant API with the aid of the django-tenant-schemas package.
    • I used the Postgres Database as the persistence layer and specifically the PostgreSQL Schemas to ensure that all tenants using the API had their data.
    • I used the REST architecture in designing my API.
    • Researched existing digital solutions and prioritized key features for app release.
    Website Links
    • https://blog.learningdollars.com/2020/08/02/how-to-implement-django-tenant-schemas-with-a-fixed-url/
    • https://agile-headland-01373.herokuapp.com/
    Github Links
    • https://github.com/MainaKamau92/rickandmortycharacters
    • https://github.com/learningdollars/mainak-django-tenant-schemas
    Qualifications
    Courses
    Data Engineering
    May 2020 - May 2020
    Udacity
    • Apache Spark
    • AWS ElasticMapReduce
    • AWS ECR
    • Data Engineering
    Natural language processing specialisation
    Sep 2020 - Dec 2020
    Cousera
    • Natural language processing
    • Twitter APIs
    • Google NLP API
    • Machine learning
    • Python
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