Aspiring Data Analyst focused on building a career in data analysis, with a special interest in cybersecurity trends.
Using machine learning to help predict the consequences of climate change for fictional company ClimateWins based in Europe. This is a project designed to challenge the junior data analyst by introducing machine learning skills in Python. The project mimics a fictional nonprofit organization (CliamteWins) with limited funding that does not have a data scientist or data engineer team. This challenge guides the analysts as a trainee, data scientist and researcher all at once to achieve ClimateWins goals.
- Steps to scale data to make it easier to use in machine learning models.
- Dendrogram and Principal Component Analysis (PCA)
- Deep Learning in Keras Convolution Neural Networks (CNN) and Recurrent Neural Networks (RNN)
- Decision Trees and Random Forest
- Hyperparameters and Tuning Models:
- Random Search
- Bayesian Search
- Handwriting Recognition with Convolution Neural Networks (CNN) & MNIST
- Radar Recognition with Generative Adversarial Networks (GAN)
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Identify weather patterns outside the regional norm in Europe.
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Determine if unusual weather patterns are increasing.
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Generate possibilities for future weather conditions over the next 25 to 50 years based on current trends.
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Determine the safest places for people to live in Europe over the next 25 to 50 years.
This data is sourced from the European Climate Assessment & Dataset (ECA&D).
The project uses weather data from 18 weather stations across Europe, covering the period from the late 1800s to 2022. The dataset includes daily observations of variables such as: -Temperature -Wind speed -Snowfall -Global radiation -And other meteorological indicators
Python β for data analysis, model building, and evaluation PowerPoint β for presenting findings and visualizations
π Notebooks
Check out my Jupyter notebooks scripts in the attached folder 'Scripts', that demonstrate my data wrangling, analysis, and visualization skills.
youtube presentation link : https://www.youtube.com/watch?v=m0KEIutMzU4&t=1s