Deep (learning) like Jacques Cousteau - Part 7 - Matrices
(TL;DR: matrices are rectangular arrays of numbers.)
Posts by Category
- R 14
- Deep-learning 11
- Mathematics 7
- Linear algebra 5
- graphs 4
- Python 4
- Life 3
- TensorFlow 3
- Software 3
- web-scraping 2
- APIs 2
- algorithms 2
- Cloud 2
- Docker 2
- Machine-learning 2
- Ranking 2
- Time-management 2
- email 1
- RStudio 1
- Images 1
- Probability 1
- Coding 1
- Data-analysis 1
- Learning 1
- Food 1
- Experiments 1
R
I walk the (train) line - part quatre - Tell me why
(TL;DR: Dijkstra’s algorithm is correct. Mathematical proof inside <3<3<3)
Deep (learning) like Jacques Cousteau - Part 6 - Dot products
(TL;DR: Start with two vectors with equal numbers of elements. Multiply them element-wise. Sum the results. This is the dot product.)
Deep (learning) like Jacques Cousteau - Part 5 - Vector addition
(TL;DR: You can add vectors that have similar dimensions.)
Deep (learning) like Jacques Cousteau - Part 4 - Scalar multiplication
(TL;DR: Multiply a vector by a scalar one element at a time.)
Deep (learning) like Jacques Cousteau - Part 3 - Vectors
(TL;DR: Vectors are ordered lists of numbers.)
Deep (learning) like Jacques Cousteau - Part 2 - Scalars
(TL;DR: Scalars are single numbers.)
Deep (learning) like Jacques Cousteau - Part 1 - Sets
(TL;DR: I’m going to go deep into deep learning. Sets are collections of things.)
RStudio’s multiple cursors rule!
(TL;DR: Come on. This is pretty short. Productivity level up by harnessing the power of RStudio!)
I walk the (train) line - part trois - Dijkstra’s revenge
(TL;DR: Author algorithmically confirms what he already knows - that there is a way to get from Newtown Station to a tasty burger. Shortest path from Newtown...
(Trying) to get to the top of R-bloggers emails
(TL;DR: Author analyses R-Bloggers emails using Gmail API. Decides on when to post to get to the top of the email list. This could either work well or fail s...
I walk the (train) line - part deux - the weight loss continues
(TL;DR: author continues to use his undiagnosed OCD for good. Breath-first search introduced on simple graph.) We learnt how to get OpenStreetMap data into ...
I walk the (train) line - part un
(TL;DR: author begins quest to use undiagnosed OCD to come up with different paths to walk to work…all in the name of weight loss) I love to walk. I’m in b...
Rent-scraping: How I saved money using R
(TD;DR: Received letter from real estate increasing my weekly rent. Reason for increase was not supported by evidence. Used R to look for evidence supporting...
Deep-learning
Learning to rank is good for your ML career - Part 2: let’s implement ListNet!
The second post in an epic to learn to rank lists of things!
Learning to rank is good for your ML career - Part 1: background and word embeddings
The first post in an epic to learn to rank lists of things!
Docker + TensorFlow + Google Cloud Platform = Love
Make your life easier by Dockerising your TensorFlow
Get deep-learnin’ on Google Cloud Platform the easy way
Create a Deep Learning VM on GCP in 2 minutes
Deep (learning) like Jacques Cousteau - Part 7 - Matrices
(TL;DR: matrices are rectangular arrays of numbers.)
Deep (learning) like Jacques Cousteau - Part 6 - Dot products
(TL;DR: Start with two vectors with equal numbers of elements. Multiply them element-wise. Sum the results. This is the dot product.)
Deep (learning) like Jacques Cousteau - Part 5 - Vector addition
(TL;DR: You can add vectors that have similar dimensions.)
Deep (learning) like Jacques Cousteau - Part 4 - Scalar multiplication
(TL;DR: Multiply a vector by a scalar one element at a time.)
Deep (learning) like Jacques Cousteau - Part 3 - Vectors
(TL;DR: Vectors are ordered lists of numbers.)
Deep (learning) like Jacques Cousteau - Part 2 - Scalars
(TL;DR: Scalars are single numbers.)
Deep (learning) like Jacques Cousteau - Part 1 - Sets
(TL;DR: I’m going to go deep into deep learning. Sets are collections of things.)
Mathematics
Deep (learning) like Jacques Cousteau - Part 7 - Matrices
(TL;DR: matrices are rectangular arrays of numbers.)
Deep (learning) like Jacques Cousteau - Part 6 - Dot products
(TL;DR: Start with two vectors with equal numbers of elements. Multiply them element-wise. Sum the results. This is the dot product.)
Deep (learning) like Jacques Cousteau - Part 5 - Vector addition
(TL;DR: You can add vectors that have similar dimensions.)
Deep (learning) like Jacques Cousteau - Part 4 - Scalar multiplication
(TL;DR: Multiply a vector by a scalar one element at a time.)
Deep (learning) like Jacques Cousteau - Part 3 - Vectors
(TL;DR: Vectors are ordered lists of numbers.)
Deep (learning) like Jacques Cousteau - Part 2 - Scalars
(TL;DR: Scalars are single numbers.)
Deep (learning) like Jacques Cousteau - Part 1 - Sets
(TL;DR: I’m going to go deep into deep learning. Sets are collections of things.)
Linear algebra
Deep (learning) like Jacques Cousteau - Part 7 - Matrices
(TL;DR: matrices are rectangular arrays of numbers.)
Deep (learning) like Jacques Cousteau - Part 6 - Dot products
(TL;DR: Start with two vectors with equal numbers of elements. Multiply them element-wise. Sum the results. This is the dot product.)
Deep (learning) like Jacques Cousteau - Part 5 - Vector addition
(TL;DR: You can add vectors that have similar dimensions.)
Deep (learning) like Jacques Cousteau - Part 4 - Scalar multiplication
(TL;DR: Multiply a vector by a scalar one element at a time.)
Deep (learning) like Jacques Cousteau - Part 3 - Vectors
(TL;DR: Vectors are ordered lists of numbers.)
graphs
I walk the (train) line - part quatre - Tell me why
(TL;DR: Dijkstra’s algorithm is correct. Mathematical proof inside <3<3<3)
I walk the (train) line - part trois - Dijkstra’s revenge
(TL;DR: Author algorithmically confirms what he already knows - that there is a way to get from Newtown Station to a tasty burger. Shortest path from Newtown...
I walk the (train) line - part deux - the weight loss continues
(TL;DR: author continues to use his undiagnosed OCD for good. Breath-first search introduced on simple graph.) We learnt how to get OpenStreetMap data into ...
I walk the (train) line - part un
(TL;DR: author begins quest to use undiagnosed OCD to come up with different paths to walk to work…all in the name of weight loss) I love to walk. I’m in b...
Python
Statistical significance intuition
An attempt at explaining a difficult concept in a characteristically dense but intuitive way
Faster web scraping with Python and asyncio
Do you use Jupyter? Are you still sending sequential web requests like a noob? Then this article is for you!
I have a problem with socks
Let’s learn how to answer the famous probability interview question involving pairs of socks.
Images as data structures: art through 256 integers
Let’s cover the basics of images as data structures, meet some psychedelic cats and ‘paint’ a hot pink chessboard using NumPy!
Life
How to plan your life
Practical lessons from Oliver Burkeman’s “Four Thousand Weeks”
An antidote to hustle culture: a better way to manage your time
Oliver Burkeman’s “Four Thousand Weeks” is already one of the best books I’ve ever read
An effort to regain control of my life through better planning
Before we begin:
TensorFlow
Learning to rank is good for your ML career - Part 2: let’s implement ListNet!
The second post in an epic to learn to rank lists of things!
Learning to rank is good for your ML career - Part 1: background and word embeddings
The first post in an epic to learn to rank lists of things!
Docker + TensorFlow + Google Cloud Platform = Love
Make your life easier by Dockerising your TensorFlow
Software
Faster web scraping with Python and asyncio
Do you use Jupyter? Are you still sending sequential web requests like a noob? Then this article is for you!
Docker and Makefiles
A whale of a time!
Render LaTeX in Google Docs
This is for all the students out there!
web-scraping
(Trying) to get to the top of R-bloggers emails
(TL;DR: Author analyses R-Bloggers emails using Gmail API. Decides on when to post to get to the top of the email list. This could either work well or fail s...
Rent-scraping: How I saved money using R
(TD;DR: Received letter from real estate increasing my weekly rent. Reason for increase was not supported by evidence. Used R to look for evidence supporting...
APIs
I walk the (train) line - part trois - Dijkstra’s revenge
(TL;DR: Author algorithmically confirms what he already knows - that there is a way to get from Newtown Station to a tasty burger. Shortest path from Newtown...
(Trying) to get to the top of R-bloggers emails
(TL;DR: Author analyses R-Bloggers emails using Gmail API. Decides on when to post to get to the top of the email list. This could either work well or fail s...
algorithms
I walk the (train) line - part quatre - Tell me why
(TL;DR: Dijkstra’s algorithm is correct. Mathematical proof inside <3<3<3)
I walk the (train) line - part trois - Dijkstra’s revenge
(TL;DR: Author algorithmically confirms what he already knows - that there is a way to get from Newtown Station to a tasty burger. Shortest path from Newtown...
Cloud
Docker + TensorFlow + Google Cloud Platform = Love
Make your life easier by Dockerising your TensorFlow
Get deep-learnin’ on Google Cloud Platform the easy way
Create a Deep Learning VM on GCP in 2 minutes
Docker
Docker and Makefiles
A whale of a time!
Docker + TensorFlow + Google Cloud Platform = Love
Make your life easier by Dockerising your TensorFlow
Machine-learning
Learning to rank is good for your ML career - Part 2: let’s implement ListNet!
The second post in an epic to learn to rank lists of things!
Learning to rank is good for your ML career - Part 1: background and word embeddings
The first post in an epic to learn to rank lists of things!
Ranking
Learning to rank is good for your ML career - Part 2: let’s implement ListNet!
The second post in an epic to learn to rank lists of things!
Learning to rank is good for your ML career - Part 1: background and word embeddings
The first post in an epic to learn to rank lists of things!
Time-management
How to plan your life
Practical lessons from Oliver Burkeman’s “Four Thousand Weeks”
An antidote to hustle culture: a better way to manage your time
Oliver Burkeman’s “Four Thousand Weeks” is already one of the best books I’ve ever read
(Trying) to get to the top of R-bloggers emails
(TL;DR: Author analyses R-Bloggers emails using Gmail API. Decides on when to post to get to the top of the email list. This could either work well or fail s...
RStudio
RStudio’s multiple cursors rule!
(TL;DR: Come on. This is pretty short. Productivity level up by harnessing the power of RStudio!)
Images
Images as data structures: art through 256 integers
Let’s cover the basics of images as data structures, meet some psychedelic cats and ‘paint’ a hot pink chessboard using NumPy!
Probability
I have a problem with socks
Let’s learn how to answer the famous probability interview question involving pairs of socks.
Coding
Learn to code for data: a pragmatist’s guide
A recipe to go from spreadsheet to code
Data-analysis
Learn to code for data: a pragmatist’s guide
A recipe to go from spreadsheet to code
Learning
Learn to code for data: a pragmatist’s guide
A recipe to go from spreadsheet to code
Food
The best bolognese recipe
Well, that was unexpected…
Experiments
Statistical significance intuition
An attempt at explaining a difficult concept in a characteristically dense but intuitive way