Muhammad Khalifa Abdullahi

Muhammad Khalifa Abdullahi

Nigeria
2K followers 500+ connections

Activity

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Experience

  • Knowtex Graphic

    Knowtex

    San Francisco, California, United States

  • -

  • -

    Mountain View, California, United States

  • -

    United States

  • -

    Lagos, Nigeria

  • -

    Zaria, Kaduna, Nigeria

  • -

    Lagos, Nigeria

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    Zaria, Kaduna, Nigeria

Licenses & Certifications

Projects

  • PyProp

    - Present

    • Built a Python library for analyzing Binomial and Gaussian distribution of a given data using the concept of OOP.
    • pyprop have methods to read data set, calculate the mean, standard deviation, probability density function, and also plots the histogram and bar chart of the data set, thereby saving alot of time for data scientist when analyzing data.
    • I uploaded the package to Pypi (Python package repository), pip install pyprop to use library

    See project
  • Super market Sales Prediction

    I made a Regression model for predicting Sale price on a Supermarket Datasets with up to 92% quality. I built this model with different types of machine learning algorithm (Decision Tree Regression, Linear Model, and DNN) by utilizing Python libraries such as Scikit-learn, Tensorflow, NumPy and Pandas.

    See project

Honors & Awards

  • First Prize Huawei ICT Competition Regional Final (Southern Africa) 2019-2020

    Huawei

  • Huawei ICT Competition 2019-2020

    Huawei Technologies

    I came Second Place in the National Finals of Huawei ICT Competition (Nigeria) on the Cloud Track.
    I Learnt about Cloud Computing, Artificial Intelligence, Big Data along other Technologies.
    I now stand a chance to represent Nigeria in the Regional Finals of the competitions in South Africa

  • Hackathon

    NITDA

    Future Hackathon NG
    I participated in the Future Hackathon NG 2019 in which we were required to solve any agricultural problem using technology
    - Lead a team of 3 to build a mobile Application for detecting and predicting Rice Leaf Diseases.
    - Acquired the datasets from kaggle, we build and trained the model using Convolutional Neural
    Network utilizing Python Libraries such as Tensorflow, Keras, and Numpy. Then convert the model
    into Tflite for mobile application…

    Future Hackathon NG
    I participated in the Future Hackathon NG 2019 in which we were required to solve any agricultural problem using technology
    - Lead a team of 3 to build a mobile Application for detecting and predicting Rice Leaf Diseases.
    - Acquired the datasets from kaggle, we build and trained the model using Convolutional Neural
    Network utilizing Python Libraries such as Tensorflow, Keras, and Numpy. Then convert the model
    into Tflite for mobile application compatibility
    - Deployed the model on a mobile app built with Kotlin. The model achieved nearly 90% accuracy on
    newer images. Our team came 3rd out of 10 teams.

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