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Achievement: StarstruckAchievement: Arctic Code Vault Contributor

Achievements

Achievement: StarstruckAchievement: Arctic Code Vault Contributor

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kennedykwangari/README.md

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🎯Kennedy Kamande Wangari is an award-winning Data Scientist, Technology Community Builder, Technology Columnist, and an AI Researcher; at the frontline, improving technical systems’ social impact and ensuring people-centric technological development for societal good.


🧭 Previously, he has worked at UNEP, NVIDIA, Xetova, and NCBA Bank to deliver high-impact data products and services –from data strategy consulting to end-to-end project implementation across the marketing, supply chain, finance, and environment fields


▶️ His work aims to pave the way towards a better understanding of the societal and environmental impacts of AI models, datasets, and systems.


As a Technology Columnist 📰✍️ he is on a mission to educate, inform, and entertain Africa about emerging technologies, trends, and developments in ways that inspire innovation.


He shares his passion for a sustainable data-literate world through public speaking opportunities, featuring in blogs, videos, workshops, research papers publications, journals, and through various media outlets: Television, Radio, and Newspapers.

Social Media Profiles:


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  1. Time-Series-Analysis-and-Forecasting-with-Python Time-Series-Analysis-and-Forecasting-with-Python Public

    The aim of the project is to provide a reference container guide of the numerous broad topics in the field of Time Series Analysis.

    Jupyter Notebook 18 7

  2. Natural-Language-Processing-with-Python Natural-Language-Processing-with-Python Public

    This repository contains data sets and code snippets on how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python!.

    Jupyter Notebook 3 1

  3. Mall-Customer-Segmentation-Data Mall-Customer-Segmentation-Data Public

    Leveraging on Unsupervised Learning Techniques (K-Means and Hierarchical Clustering Implementation) to Perform Market Basket Analysis: Implementing Customer Segmentation Concepts to score a custome…

    Jupyter Notebook 15 11

  4. Cohort-Analysis-and-Customer-Segmentation-with-Python Cohort-Analysis-and-Customer-Segmentation-with-Python Public

    We are tasked to Perform Cohort and Recency Frequency and Monetary Value Analysis to understand the value derived from different customer segments. Further, we will divide customers in different cl…

    Jupyter Notebook 6 1

  5. -Facebook-Friend-Recommendation-using-Graph-Mining -Facebook-Friend-Recommendation-using-Graph-Mining Public

    In this challenge we have given a directed social graph, and we have to predict missing links to recommend users (Link Prediction in graph)

    Jupyter Notebook 3

  6. Interpretable-Machine-Learning- Interpretable-Machine-Learning- Public

    Extracting human-understandable insights from any machine learning model. Exploring various MLI (Machine Learning Interpretability) techniques that help us debug, decode, get good accuracy and expl…

    Jupyter Notebook 1