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This is Ian Ozsvald's blog (@IanOzsvald), I'm an entrepreneurial geek, a Data Science/ML/NLP/AI consultant, author of O'Reilly's High Performance Python book, co-organiser of PyDataLondon, a Pythonista, co-founder of ShowMeDo and also a Londoner. Here's a little more about me.

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27 January 2017 - 13:06Introduction to Random Forests for Machine Learning at the London Python Meetup

Last night I had the pleasure of returning to London Python to introduce Random Forests (this builds on my PyConUK 2016 talk from September). My goal was to give a pragmatic introduction to solving a binary classification problem (Kaggle’s Titanic) using scikit-learn. The talk (slides here) covers:

  • Organising your data with Pandas
  • Exploratory Data Visualisation with Seaborn
  • Creating a train/test set and using a Dummy Classifier
  • Adding a Random Forest
  • Moving towards Cross Validation for higher trust
  • Ways to debug the model (from the point of view of a non-ML engineer)
  • Deployment
  • Code for the talk is a rendered Notebook on github

I finished with a slide on Community (are you contributing? do you fulfill your part of the social contract to give back when you consume from the ecosystem?) and another pitching PyDataLondon 2017 (May 5-7th). My colleague Vincent is over from Amsterdam – he pitched PyDataAmsterdam (April 8-9th). The Call for Proposals is open for both, get your talk ideas in quickly please.

I’m really happy to see the continued growth of the London Python meetup, this was one of the earliest meetups I ever spoke at. The organisers are looking for speakers – do get in touch with them via meetup to tell them what you’d like to talk on.

Ian applies Data Science as an AI/Data Scientist for companies in ModelInsight, sign-up for Data Science tutorials in London. Historically Ian ran Mor Consulting. He also founded the image and text annotation API Annotate.io, co-authored SocialTies, programs Python, authored The Screencasting Handbook, lives in London and is a consumer of fine coffees.

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