Googlielmo's blog

 I just realized that I am using Streamlit since almost one year now, posted about in Twitter or LinkedIn several times, but never wrote a blog post about it before. Communication in Data Science and Machine Learning is the key. Being able to showcase work in progress and share results with the business makes the difference. Verbal and non-verbal communication skills are important. Having some tool that could support you in this kind of conversation with a mixed audience that couldn't have a technical background or would like to hear in terms of results and business value would be of great help. I found that Streamlit fits well this scenario. Streamlit is an Open Source (Apache License 2.0) Python framework that turns data or ML scripts into shareable web apps in minutes (no kidding). Python only: no front‑end experience required. To start with Streamlit, just install it through pip (it is available in Anaconda too): pip install streamlit and you are ready to execute the working de...

  Faker is an Open Source Python package that generates synthetic data that could be used for many things such as populating a database, do load testing or anonymize production data for development or ML purposes. Generating fully random data isn't a good choice: with Faker you can drive the generation process and tailor the generated data to your specific needs: this is the greatest value provided by Faker. This package comes with 23 built-in data providers, some other providers are available from the community. The available data providers cover majority of data types and cases, but it is possible any way make the generated data more meaningful by implementing a custom provider. Faker supports Python 3.6+ and it is available for installation through PyPI or Anaconda.  Here's a code example that shows how to implement a custom provider to generate synthetic data following the structure and constraints as for this Kaggle  dataset related to a restaurant data with consumer...

 I am back to the blog after some months where I have been pretty busy with interesting and challenging projects and coping with the new "normal" of the COVID-19 era.  Lot of things happened and I have several stuff to share in the upcoming months. Today I am going to speak at the Big Things 2020, the Data and AI conference. This year it moved virtual. Registration is still open and for free. I hope you have a chance to attend my talk at 7:45 PM GMT+1. I am going to discuss about Adversarial Attacks to Computer Vision systems and mitigation strategies. I hope to meet you there and do also some networking in the dedicated chat area. Follow-ups for this topic will be shared in this blog in the upcoming weeks.

I am so excited to be attending the Shift AI conference this April in Dublin! It's @shiftconf_co 's #ArtificialIntelligence conference where we will discuss the newest technologies in data mining, machine learning and neural networks. While Ireland is a very active hub for AI in Europe, so far there has been a lack of good conferences happening here: so, Shift AI is welcome! I hope to see you at the event. Learn more over at https://ctt.ec/2K2o6+

If you are interested on hearing more about some way to do predictions of Apache Spark applications performance, please join tomorrow's Dublin Data Science Festival Meetup  which would start at 6 PM  local time at the Walmart Labs place . Two talks in agenda, the first one from Mirko Arnold (Walmart Labs) about Computer Vision and the second one from me. It would also be another great opportunity for networking.

Another interesting Hadoop User Group (HUG) Ireland Meetup next week (Monday October 3rd 2016) in Dublin at the Bank of Ireland premises in Grand Canal Square :   http://www.meetup.com/it-IT/hadoop-user-group-ireland/events/234240469/?eventId=234240469&chapter_analytics_code=UA-55809013-2 If you are in the Dublin area on Monday and interested in Machine Learning, please attend this event to learn more and start networking with other Big Data professionals. Hope to meet you there!