This repository contains my notebooks and projects from the IBM AI Engineering Professional Certificate course on Coursera.
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Updated
Jun 24, 2024 - Jupyter Notebook
This repository contains my notebooks and projects from the IBM AI Engineering Professional Certificate course on Coursera.
This repository contains all notebooks and notes from the IBM Data Science Professional Certification.
A collection of Jupyter notebooks guiding you from theoretical concepts of Quantum Information to practical implementations with Qiskit.
Several Python and R scripts, notebooks... that might be useful when studying Data Science
My notebooks for QGSS 2023
Data Analysis with Python course Jupyter notebooks
This is my capstone project from the IBM Data Analyst course. In each analytics process, the data is stored in the Jupyter notebooks that are uploaded. Week 1 in the project is data collection; 2 is data wrangling, 3 is exploratory data analysis, 4 is Data visualisation, 5 is Building a dashboard and the last week is Presentation of findings.
Infuse AI into your application. Create and deploy a customer churn prediction model with IBM Cloud Private for Data, Db2 Warehouse, Spark MLlib, and Jupyter notebooks.
This repository contains all my notebooks, lab solutions, and assignments for the IBM Machine Learning Course.
Run a Jupyter Notebook to detect, track, and count cars in a video using Maximo Visual Insights (formerly PowerAI Vision) and OpenCV
An integration of H2O Sparkling Water as a notebook for IBM Spectrum Conductor.
This notebook is in the area of People Analytics and includes the analysis of the IBM dataset to identify attrition. Besides attrition I also focus on diversity. I created strategies to reduce attrition.
A JupyterLab extension that displays IBM Cloud offerings and other promotional material in JupyterLab notebooks.
Data analysis, model building, and deploying with Watson Machine Learning with notebook
A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.
A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.
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