Posts by Tags

algorithms

Eyespot

5 minute read

Published:

What are these spots?

In a recent survey doctors were required to take pictures of patients’ eyes and look for brigh local spots in the middle region of the cornea. There can be about one/tow hundreds possible spots in a single cornea image; these spots can be of very different size, and more over they have not the same color. screenshotA sample image of a patient right eye It has been seen that a well-trained doctor can find all the spots in about 40 minutes; this Java tool can mark them in 2 seconds.

bitcoin

Crypto money: the bubble

7 minute read

Published:

Foreword

If you are interested in the technical side, please note that there are many smarter people than me who have written better guides regarding this topic. You may start here. These are my personal ideas which I want to share because so many of my friends got interested and ask me the same questions. No inner, dark motivations involved.

crypto

Crypto money: the bubble

7 minute read

Published:

Foreword

If you are interested in the technical side, please note that there are many smarter people than me who have written better guides regarding this topic. You may start here. These are my personal ideas which I want to share because so many of my friends got interested and ask me the same questions. No inner, dark motivations involved.

facebook

Spotted Unipd: machine-learn your sweet half

3 minute read

Published:

What is this? Another Facebook-sentiment analysis?

What can you do with ~5000 posts just downloaded from one of the most visited Facebook pages where Unipd students chat about (true) love? The correct answer should be: simply sentiment-analyze them! Yet, there are few drawbacks:

  1. few (but there are some) posts are not in Italian, they are written in other languages: some dialects, English …
  2. the meaning is very easy to understand, and the content does not vary much among different posts
  3. the typical post is 45 words long and each of them is about 5 chars long, so there is not much data to deal with and find something really interesting about the opinions of the writers
  4. furthermore the style is so much different among posts: one post maybe all sad and depressed while the next can be extremely happy and joyful

fiat

Crypto money: the bubble

7 minute read

Published:

Foreword

If you are interested in the technical side, please note that there are many smarter people than me who have written better guides regarding this topic. You may start here. These are my personal ideas which I want to share because so many of my friends got interested and ask me the same questions. No inner, dark motivations involved.

garmin

When Garmin Connect is not enough

2 minute read

Published:

What is this? Another scraper?

First off, as simple as possible: pygce is a python script to download and analyze your data from your Garmin Connect dashboard.

  • it’s not a simple scraper, because it’s also a bot which handles webpage stuff
  • it’s not a common machine-learning program, because it provides all the tools to retrieve the dataset
  • it’s not an illegal data-fetcher/russian virus parser, because it’s the user only who provides the credentials and run the script
  • it’s not a bot, since it provides also APIs and models to deal with common Garmin Connect features

java

Introducing HAL

less than 1 minute read

Published:

Behold the power of the library!

I always wanted to have a library to use like from my_awesome_library import anything; anything.do_anything(). Now it’s (almost) possible. With JHal and PyHal you’re not gonna believe what you can do.

Eyespot

5 minute read

Published:

What are these spots?

In a recent survey doctors were required to take pictures of patients’ eyes and look for brigh local spots in the middle region of the cornea. There can be about one/tow hundreds possible spots in a single cornea image; these spots can be of very different size, and more over they have not the same color. screenshotA sample image of a patient right eye It has been seen that a well-trained doctor can find all the spots in about 40 minutes; this Java tool can mark them in 2 seconds.

library

Introducing HAL

less than 1 minute read

Published:

Behold the power of the library!

I always wanted to have a library to use like from my_awesome_library import anything; anything.do_anything(). Now it’s (almost) possible. With JHal and PyHal you’re not gonna believe what you can do.

machine-learning

Spotted Unipd: machine-learn your sweet half

3 minute read

Published:

What is this? Another Facebook-sentiment analysis?

What can you do with ~5000 posts just downloaded from one of the most visited Facebook pages where Unipd students chat about (true) love? The correct answer should be: simply sentiment-analyze them! Yet, there are few drawbacks:

  1. few (but there are some) posts are not in Italian, they are written in other languages: some dialects, English …
  2. the meaning is very easy to understand, and the content does not vary much among different posts
  3. the typical post is 45 words long and each of them is about 5 chars long, so there is not much data to deal with and find something really interesting about the opinions of the writers
  4. furthermore the style is so much different among posts: one post maybe all sad and depressed while the next can be extremely happy and joyful

medicine

Eyespot

5 minute read

Published:

What are these spots?

In a recent survey doctors were required to take pictures of patients’ eyes and look for brigh local spots in the middle region of the cornea. There can be about one/tow hundreds possible spots in a single cornea image; these spots can be of very different size, and more over they have not the same color. screenshotA sample image of a patient right eye It has been seen that a well-trained doctor can find all the spots in about 40 minutes; this Java tool can mark them in 2 seconds.

nlp

Spotted Unipd: machine-learn your sweet half

3 minute read

Published:

What is this? Another Facebook-sentiment analysis?

What can you do with ~5000 posts just downloaded from one of the most visited Facebook pages where Unipd students chat about (true) love? The correct answer should be: simply sentiment-analyze them! Yet, there are few drawbacks:

  1. few (but there are some) posts are not in Italian, they are written in other languages: some dialects, English …
  2. the meaning is very easy to understand, and the content does not vary much among different posts
  3. the typical post is 45 words long and each of them is about 5 chars long, so there is not much data to deal with and find something really interesting about the opinions of the writers
  4. furthermore the style is so much different among posts: one post maybe all sad and depressed while the next can be extremely happy and joyful

parser

When Garmin Connect is not enough

2 minute read

Published:

What is this? Another scraper?

First off, as simple as possible: pygce is a python script to download and analyze your data from your Garmin Connect dashboard.

  • it’s not a simple scraper, because it’s also a bot which handles webpage stuff
  • it’s not a common machine-learning program, because it provides all the tools to retrieve the dataset
  • it’s not an illegal data-fetcher/russian virus parser, because it’s the user only who provides the credentials and run the script
  • it’s not a bot, since it provides also APIs and models to deal with common Garmin Connect features

python

Introducing HAL

less than 1 minute read

Published:

Behold the power of the library!

I always wanted to have a library to use like from my_awesome_library import anything; anything.do_anything(). Now it’s (almost) possible. With JHal and PyHal you’re not gonna believe what you can do.

running

When Garmin Connect is not enough

2 minute read

Published:

What is this? Another scraper?

First off, as simple as possible: pygce is a python script to download and analyze your data from your Garmin Connect dashboard.

  • it’s not a simple scraper, because it’s also a bot which handles webpage stuff
  • it’s not a common machine-learning program, because it provides all the tools to retrieve the dataset
  • it’s not an illegal data-fetcher/russian virus parser, because it’s the user only who provides the credentials and run the script
  • it’s not a bot, since it provides also APIs and models to deal with common Garmin Connect features

scraper

Spotted Unipd: machine-learn your sweet half

3 minute read

Published:

What is this? Another Facebook-sentiment analysis?

What can you do with ~5000 posts just downloaded from one of the most visited Facebook pages where Unipd students chat about (true) love? The correct answer should be: simply sentiment-analyze them! Yet, there are few drawbacks:

  1. few (but there are some) posts are not in Italian, they are written in other languages: some dialects, English …
  2. the meaning is very easy to understand, and the content does not vary much among different posts
  3. the typical post is 45 words long and each of them is about 5 chars long, so there is not much data to deal with and find something really interesting about the opinions of the writers
  4. furthermore the style is so much different among posts: one post maybe all sad and depressed while the next can be extremely happy and joyful

When Garmin Connect is not enough

2 minute read

Published:

What is this? Another scraper?

First off, as simple as possible: pygce is a python script to download and analyze your data from your Garmin Connect dashboard.

  • it’s not a simple scraper, because it’s also a bot which handles webpage stuff
  • it’s not a common machine-learning program, because it provides all the tools to retrieve the dataset
  • it’s not an illegal data-fetcher/russian virus parser, because it’s the user only who provides the credentials and run the script
  • it’s not a bot, since it provides also APIs and models to deal with common Garmin Connect features

unipd

Spotted Unipd: machine-learn your sweet half

3 minute read

Published:

What is this? Another Facebook-sentiment analysis?

What can you do with ~5000 posts just downloaded from one of the most visited Facebook pages where Unipd students chat about (true) love? The correct answer should be: simply sentiment-analyze them! Yet, there are few drawbacks:

  1. few (but there are some) posts are not in Italian, they are written in other languages: some dialects, English …
  2. the meaning is very easy to understand, and the content does not vary much among different posts
  3. the typical post is 45 words long and each of them is about 5 chars long, so there is not much data to deal with and find something really interesting about the opinions of the writers
  4. furthermore the style is so much different among posts: one post maybe all sad and depressed while the next can be extremely happy and joyful