Pier Paolo Ippolito

Data Scientist

Pier Paolo Ippolito is a Data Scientist and MSc in Artificial Intelligence graduate from the University of Southampton. He has a strong interest in AI advancements and machine learning applications (such as finance and medicine). Connect with him on Linkedin.

Design Patterns in Machine Learning for MLOps

By Pier Paolo Ippolito, Data Scientist on February 23, 2022 in MLOps
This article outlines some of the most common design patterns encountered when creating successful Machine Learning solutions.
Paradoxes in Data Science

By Pier Paolo Ippolito, Data Scientist on September 17, 2021 in Data Science, Statistics
Have a look into some of the main paradoxes associate with Data Science and it’s statistical foundations.
Getting Started with Reinforcement Learning

By Pier Paolo Ippolito, Data Scientist on April 26, 2021 in AI, Beginners, Reinforcement Learning
Demystifying some of the main concepts and terminologies associated with Reinforcement Learning and their association with other fields of AI.
Roadmap to Computer Vision

By Pier Paolo Ippolito, Data Scientist on October 26, 2020 in Computer Vision, Convolutional Neural Networks, Data Preprocessing, Neural Networks, Roadmap
Read this introduction to the main steps which compose a computer vision system, starting from how images are pre-processed, features extracted and predictions are made.
Roadmap to Natural Language Processing (NLP)

By Pier Paolo Ippolito, Data Scientist on October 19, 2020 in Data Preprocessing, LDA, NLP, Python, Roadmap, Sentiment Analysis, Transformer, Word Embeddings
Check out this introduction to some of the most common techniques and models used in Natural Language Processing (NLP).
Getting Started with PyTorch

By Pier Paolo Ippolito, Data Scientist on October 14, 2020 in Neural Networks, Python, PyTorch
A practical walkthrough on how to use PyTorch for data analysis and inference.
Probability Distributions in Data Science

By Pier Paolo Ippolito, Data Scientist on February 26, 2020 in Data Science, Distribution, Normal Distribution, Probability
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
Getting Started with R Programming

By Pier Paolo Ippolito, Data Scientist on February 19, 2020 in Data Science, Machine Learning, Programming, R
An end to end Data Analysis using R, the second most requested programming language in Data Science.
Optimal Estimation Algorithms: Kalman and Particle Filters

By Pier Paolo Ippolito, Data Scientist on February 5, 2020 in Kalman Filters, Machine Learning, Probability
An introduction to the Kalman and Particle Filters and their applications in fields such as Robotics and Reinforcement Learning.
Understanding Cancer using Machine Learning

By Pier Paolo Ippolito, Data Scientist on August 16, 2019 in Cancer Detection, Healthcare, Machine Learning, Medical
Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.

Pier Paolo Ippolito

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