Jordy Snijders

Software Engineer
Cloud Specialist
Data Scientist

Machine Learning

My Masters of Science (MSc) degree means that I had a formal education in data collection/processing/analysis; statistics and machine learning. Next to that, I have built and deployed many data science projects with the following internationally popular frameworks and libraries that are industry standards these days.

Python
Python
for machine learning, data science
TensorFlow
TensorFlow
for running neural networks in production
Keras
Keras
for high level API access to TensorFlow
PyTorch
PyTorch
for prototyping with neural networks
Scikit-Learn
Scikit-Learn
for classification, regression, clustering

Data Science

Data collection. Dataset loading. Dimensionality reduction. Value processing. Standardization and normalization. Feature engineering. Plotting informative graphs. Etcetera.

Jupyter
Jupyter
for interactive Python sessions
Pandas
Pandas
for data loading, analysis
NumPy
NumPy
for numerical computations
SciPy
SciPy
for scientific computations
MatplotLib
MatplotLib
for high quality 2D plots

Managed Solutions

Neural networks, classifiers, regressors and clustering algorithms. I've delivered and deployed them all. Often with the use of the following managed tools:

Colab
Colab
for interactive Python sessions
Google ML Engine
Google ML Engine
for running finalized models in production
Google AutoML
Google AutoML
for computer vision, natural language
AWS SageMaker
AWS SageMaker
for running finalized models in production
AWS Rekognition
AWS Rekognition
for image and video analysis