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Blog

Quantified-Self: The Power of Day One & Launch Center Pro

Mickael Le Gal

If you like to keep track of the things you do during the day like your workout, your meals, your sleep but haven't found a solution to make it effortless and keep it all in one place, here is an easy way to do it using Day One and Launch Center Pro. I found out about this workflow last week while reading Josiah Wiebe's blog and this has changed the way I journal and log the different activities I want to track. In this post, I'll you show you how to set up a Day One action with Launch Center Pro and how to personalize it.

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Working out in America's Healthiest Cities

Mickael Le Gal

In this post, I will take a look at the fitness clubs of America's healthiest cities (see full list below). I was curious to see what these cities were offering in terms of gyms and other indoor workout facilities, I also wanted to know the type of sports people were into and where were located the sporty neighborhoods. 

I've used Foursquare’s API to collect information (geolocation, total number of users, category) on the fitness centres of each city. Note that for this article, I will mainly focus on the indoor fitness facilities and more particularly on Gyms, Yoga Studios and Martial Art Dojos as the data for these categories was more consistent across cities. 

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Eat, Play, Love (Maybe) in San Francisco

Mickael Le Gal

When discovering a new city, I usually prefer to toss the map and wander around town rather than limiting myself to the most touristic spots. This way, I get a better sense of the place's atmosphere and of what it's like to live there. Yes I won't deny that I got lost a few times and felt stupid I didn't bring the map but that's ok, I've always found nice people to help me find my way. Now, if you have a limited amount of time and just want to see the city's most vibrant areas, how do you know where to go first? 

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How to build a recommendation system

Mickael Le Gal

Have you ever wondered how Amazon was breaking in your wallet by suggesting products that you couldn’t resist buying? How Netflix found this awesome movie that you love? Well, it’s all part of the magic that goes into their recommendation systems. These recommenders are developed to find patterns in your preferences, search for similar patterns in other people and make relevant suggestions that will encourage you to spend more on the company's products and services. In this post, I’ll explain the basic idea behind a recommender system and how to build a simple one based on book reviews of the 1 million book ratings database.

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