“From NLP a helpful tool for teaching”
On 20th May 2021, Data Science Milan has organized a webMeetup hosting Ramsri Goutham to talk about Questgen, an open-source library used for Multiple Choice Questions generation.
“Question generation using NLP by QuestGen.AI”, by Ramsri Goutham, CTO of QuestGen.AI
Ramsri explained QuestGen open-source library used to generate questions automatically from text. The intuition is coming from the needs to create a tool to automate the assessment process helping teachers in their job. This tool is able to generate from an article/text: Multiple Choice Questions (MCQs), true or false questions, FAQs, paraphrasing, and question…
“Life is easier with AWS services”
On 21st April 2021, Data Science Milan has organized a webMeetup hosting Francesco Marelli to talk about data manipulation pipelines with AWS.
“Speed up data preparation for ML pipelines on AWS”, by Francesco Marelli, Senior Solutions Architect at AWS.
To exploit huge amounts of data, Companies move all their data from various silos into a single location, called a data lake, to perform analytics and Machine Learning. Francesco showed the Lake House Architecture on AWS. The idea behind this architecture is to build a central repository of data upon which different analytics services, from…
“Towards an innovation world”
On 18th February 2021, Data Science Milan has organized a webMeetup in collaboration with Democratize AI, hosting Professor Francesco Calimeri to talk about Artificial Intelligence topic.
“DLVSystem: Artificial Intelligence and Technology Innovation from Calabria”, by Francesco Calimeri, Professor at the Calabria University from Department of Mathematics and Informatics, partner in DLVSystem.
Prof. Calimeri has started introducing the Artificial Intelligence concept in the way thought by people: machines that can become humans, machines with human behaviour and emotions. Actually, Artificial Intelligence is a discipline focused on comprehension and replication of intelligent behaviours. The term of Artificial Intelligence…
“…for a better data science activity”
On 26th January 2021, Data Science Milan has organized a webMeetup hosting Michael Munn to talk about “Machine Learning Design Patterns” book which is a co-author. Topics of the talk: Rebalancing, Useful Overfitting and Explainable Predictions.
“Machine Learning Design Patterns”, by Michael Munn, ML Solutions Engineer at Google
“Opportunities from Cloud”
On 15th December 2020 Data Science Milan has organized a webMeetup hosting Gianmario Spacagna and Luc Mioulet to talk about Helixa Machine Learning end-to-end system platform.
“Serverless Machine Learning architectures and engineering practices at Helixa”, by Gianmario Spacagna, Chief Scientist at Helixa, and Luc Mioulet, ML Engineer at Helixa
The talk has been split into three parts: 1) serverless services available in AWS; 2) Helixa Machine Learning platform; 3) Map/Reduce serverless architecture.
Gianmario started introducing the concept of serverless and an overview about serverless services available in AWS.
In the traditional way when we want to build…
“from word2vec to prod2vec”
On 24th November 2020 Data Science Milan has organized a webMeetup hosting Jacopo Tagliabue and Christine Yu to talk about the scalable solution to train “product embeddings” in e-commerce shopping, a new way in which neural network understand and process products.
“The Embeddings that came in from the Cold”, by Jacopo Tagliabue, Lead AI Scientist at Coveo, and Christine Yu, ML Developer at Coveo
Jacopo started introducing the embedding concept. Word Embedding is a method of extracting features out of text, to represent words in a lower-dimensional space by numeric vectors input that can be used…
“Beyond Data Science”
On 21st July 2020 Data Science Milan has organized a webMeetup hosting Stephen Wendel to talk about Behavioural Science.
Grasp your free copy of the workbook: “Designing for Behavior Change” here.
“Behavioral Science for Data Scientists”, by Stephen Wendel, Head of Behavioral Science at Morningstar
Behavioural Science is a fascinating field and it’s rapidly growing. Data Science has been grown very quickly for about 15–20 years, meanwhile Behavioural Science started about 10 years ago.
Stephen has started the talk introducing what is Behavioural Science.
Behavioural scientists know all about the human brain. They are specialized in cognitive…
“Towards Artificial Intelligence”
On 30th June 2020, Data Science Milan has organized a webMeetup hosting Marco Del Pra, an Artificial Intelligence Specialist, to talk about Reinforcement Learning.
“Reinforcement Learning Overview”, by Marco Del Pra, Freelancer
Reinforcement Learning, is the area of Machine Learning that deals with sequential decision-making, it can be described as a Markov decision process.
There are three basic concepts in Reinforcement Learning: state, action, and reward. The state describes the current situation. The action is what an agent can do in each state. The reward describes the feedback from the environment which can be positive or even…
“Feature Store to improve a Data Science Workflow”
On 4th June 2020 Data Science Milan has organized a webMeetup hosting Fabio Buso, Head Engineer, to talk about MLOps with Feature Store topic.
“MLOps with Feature Store: Filling the Gap in ML Infrastructure”, by Fabio Buso, Head Engineer at Logical Clocks
MLOps (Machine Learning Operations) can be tought as an extension of DevOps (Software Developement Operations) with the goal to merge both ML applications development and operation from ML applications, making easier to deploy models frequently.
MLOps with Feature Store borns from the idea to apply software engineering development to Machine…
“Beyond the usual Time Series”
On 5th May 2020 Data Science Milan has organized a webMeetup hosting Marco Del Pra, an Artificial Intelligence Specialist, to talk about time series classification topic.
“Time Series Classification with Deep Learning”, by Marco Del Pra, Freelancer
Usually time series are used for forecasting demand or sales of a product. Given the amount of temporal data being increases exponentially, was born the opportunity to experiment new ideas and algorithms with time series. Some time series classification use cases come from ECG/EEG analysis, Image Classification, Classifying Motion Sensor Data, Cyber Security, Anomaly Detection.
A time series…