About

I’m a Data Science consultant based in London, UK.

I help companies making sense of their data using Data Science and Machine Learning, and bringing their R&D efforts in production.

I’m an international conference speaker and trainer, an author with Packt Pub, and a co-organiser of the PyData London meet-up and conference series.

Backed by a PhD in Information Retrieval, I specialise in search applications and text analytics applications, and I’ve enjoyed working on a broad range of information management and data science projects.

I’m experienced in the design and implementation of applications including enterprise search, semantic search, vertical search, text summarisation, sentiment analysis, text classification/clustering and recommender systems.

Some of the technologies I use on a regular basis include:
Python
– NumPy, SciPy, NLTK, gensim, pandas, scikit-learn
– Elasticsearch, Lucene, NoSQL, SQL

I’m happy to discuss opportunities for a technical contracting role as well as strategic consultancy.

Follow me on Twitter: @marcobonzanini

Connect via LinkedIn: uk.linkedin.com/in/marcobonzanini

6 thoughts on “About

  1. Marco,

    I’m doing a side project for my personal website, and it involves language processing and semantic orientation, so I found your blog series and am trying to follow along; basically I adapted your twitter analyzer for reddit, and am using it to analyze my own comments, however I’m not sure I’m implementing it correctly…when it comes to co-occurrence, I’m getting useless combos like ((‘unpaused’, ‘whoever’), 1), etc.

    I was wondering if you could help me understand it a little better. I can send over my code and everything if you want to look it over or have the time.

    Like

  2. Hi Marco,

    I was having trouble following along in your “Mastering Social Media Mining with Python”. In chapter 2, when attempting to set my environmental variables in Mac OSX in a bash shell, I set them with:

    export TWITTER_CONSUMER_KEY=
    export TWITTER_CONSUMER_SECRET=
    export TWITTER_ACCESS_TOKEN=
    export TWITTER_ACCESS_TOKEN_SECRET=

    But when I try to run the next code snippet:

    from tweepy import Cursor
    from twitter_client import get_twitter_client

    if __name__ == ‘__main__’:
    client = get_twitter_client()

    for status in Cursor(client.home_timeline).items(10):
    # Process a single status
    print(status.text)

    I get the key error:

    TWITTER_* environment variables not set

    Please help!

    Like

    1. Hi David,
      with the command:
      export VARIABLE=
      (with nothing after the symbol “=”) you’re un-setting its value, instead you need to pass the value with:
      export VARIABLE=”put-your-value-here”
      and you can see if the value is correctly set with the command:
      echo $VARIABLE
      (of course replace VARIABLE with the four TWITTER_* variables)

      In macOS, you can also add the four export commands at the end of your ~/.bash_profile file, so the commands are executed automatically when you open a new shell.

      Cheers,
      Marco

      Like

  3. Just finished Data Analysis with Python! Great learning experience for gaining applicable and functional use of python as a data science tool. It’s to the point, clear and without filler. Looking forward to the next edition soon. What other titles would you recommend after completing this video course?

    Like

    1. Hi, thanks for the nice words. I have another video course with PacktPub coming up soon, it covers a number of data science recipes with Python, somehow it’s a follow up of the first course although they are independent products, I’ll put an update on this blog and on my Twitter when it’s out. My book Mastering Social Media Mining with Python is focused on how to analyse data from social media platforms using Python, and it touches different aspects of data analysis, data mining, machine learning and natural language processing. If you want to dig more into machine learning, another good book is Python Machine Learning also published by PacktPub.

      Cheers,
      Marco

      Like

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