Software should be optimized for the domain it is performing in, or else it will turn into an unmaintainable nightmare for both developers and domain experts.
The Dream Machine
How the modern computer came to be, courtesy of the visionary JCR Licklider. Incredible. None of this was an accident.
Machine Learning Guide
30 Episodes of Machine Learning content. Best audio resource I've found.
Machine Learning Engineering in Ten Parts
Machine Learning Engineering in Ten Parts, with Paper Club
Augmenting Long-term Memory
The paper that got me into Anki and spaced repetition. Has 10x'd my studying efficiency and retention.
Languages, Compilers and Interpreters
Lecture notes from Bradfield's languages class
Lecture notes from Bradfield's networking class
Analyzing 50k fonts using deep neural networks
Perfect dataset for training fonts, trained model even has 40 latent factors.
Startup School 2018
Startup School: How to start a startup. Talks from big YC founders and partners.
How to deliver on Machine Learning projects
Step-by-step pipeline from idea to production for an ML project
Lecture notes from Bradfield's databases class
Lecture notes from Bradfield's distributed systems class
Artificial Intelligence: The Revolution Hasn't Happened Yet
Human-imitative AI is not a good way to frame current progress in AI. Intelligence Augmentation and Intelligence Infrastructure present an equally important (and as-yet-unnamed) class of problems.
Mathematics for Computing
Lecture notes from Bradfield's math class
101: Ben Orenstein - How to Build an App in a Week
Be ruthless about cutting and be flexible about scope. Set hard deadlines.
Lecture notes from Bradfield's operating systems class
What Truly Makes a Senior Developer
Senior developers understand that nothing is without possible issues, downsides, and risks.
Documents OCR: Improving Efficiency by Making PDFs Searchable
Use Google Cloud Vision. Good OCR pipeline reference for startup.
Part 4: Types of Accounts
Types of Financial Accounts in PM Accounting
Part 2: Double-Entry Bookkeeping
Double Entry Bookkeeping in PM Accounting
Web Architecture 101
Walkthrough of Web Application Architecture
Reality Driven Development
Kanban + light pairing will give you a flexible, reality driven approach to achieving the real goal that's driving your business: delivering as much value as possible as fast as possible.
Who is MiningLamp? Why was it able to win Tencent's high-value investment?
MiningLamp has gotten significant attention and investment for its police-assisting AI.
Winograd Schema Challenge
The Winograd Schema Challenge aims to address the flaws in the Turing Test to determine if an AI is "human level".
Markov Decision Processes
Markov Decision Processes are Finite State Machines with four key components: state, action, transition function, reward function. They run into the curse of dimensionality.
Lots of good architecture advice (not all JS-specific!) from a JS architect at Google
How I Learned to Stop Worrying and Love the State Machine
Any reasonably complex domain object degenerates into a state machine, so you might as well get ahead of the curve.
Code Smells: Mutation
Make things immutable as much as you can!
Code Smells: Multi Responsibility Methods
Methods should do one thing. Extract things until this is the case.
Code Smells: Null
All about the Null code smell. Use `Optional`, `@NotNull` to combat it.
Fellow Engineers: This is where your money comes from.
Your customers make you money, so if you care about money care about your customers.
Variational Autoencoders Explained
Variational autoencoders are generative encoder-decoder networks with a constraint on the encoding network. Well-explained.
Approaching (Almost) Any Machine Learning Problem
Mental model for approaching ML problems. Very good breakdown.
Effective Java, 2nd Edition
Very good grab bag of tips and tricks for Java. Many were immediately applicable. Explained at the perfect level of abstraction for me.
AI Index Thoughts
Thoughts on the AI Index
AI Index Index
Summarizing a summary of the state of AI
From Research To Practice
Notes on Best Practices for Applying Deep Learning to Novel Applications
Language Modeling Survey
Notes on Exploring the Limits of Language Modeling
Notes on Bag of Tricks for Efficient Text Classification
GRUs vs. LSTMs
Notes on Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
The Pragmatic Programmer
Collection of somewhat common sense but well-stated programming advice.
Patterns of Enterprise Application Architecture
Solid set of backbone concepts for enterprise applications. Many of his ideas have developed a lot since this book was released in 2002 but it strengthened my understanding to see them explained firsthand.
Reinforcement learning is a type of unsupervised state-action-transition-reward training mainly used to learn games right now.
Reproducibility and the Philosophy of Data with Clare Gollnick - TWiML Talk #121
Studies are not reproducible and it's not a good look for the industry. Solution: do real research, don't just throw stuff at a wall and see what sticks.
Optimal decision-making with POMDPs
POMDPs are Markov decision processes that have to deal with a partially obervable game.
Bayesian Methods For Hackers
The simplest explanation of Bayesian methods and probabilistic programming I've come across. Says a lot about the field that this book was still extremely difficult to get through.
Newcastle University MAS2317/3317: Introduction to Bayesian Statistics
Notes taken from lecture notes from Newcastle University Bayesian Statistics course, with James from Paper Club
False Discovery Rates
How to reduce the noise of making multiple comparisons.
Be more rigorous in real life by thinking in terms of priors, posteriors, and updates.
From Research to Startup, There and Back Again
Decades of experience in Silicon Valley with John Hennessy (current chairman of Alphabet)
Some Code I Deleted
Always look for existing well-written, well-tested code before embarking on your own adventure. No code is better than no code.
Code Smells: Too Many Problems
Break the method into smaller pieces. Work on one smell at a time. Step back, get a bigger picture to model the problem. Introduce new domain objects if appropriate. Document your changes.
Code Smells: If Statements
Avoid crazy conditionals by moving them to the correct place, collapsing them, extracting to methods
Code Smells: Deeply Nested Code
Deeply nested code is bad. Encapsulate, use streams.
Google Rules of Machine Learning
Bite-size, Google-scale advice for ML.
The UX of AI
Machine learning should be human-centered
The cold start problem: how to build your machine learning portfolio
Build a project with an interesting dataset that took obvious effort to collect, and make it as visually impactful as possible.
On Being an Engineering Manager
Grab bag of wisdom on engineering management
AWS, MongoDB, and the Economic Realities of Open Source
Open Source financials echo those of the music industry; what's being sold is not the software, but the packaging. This is dangerous if left unaddressed.
Core Java Volume 1 -- Fundamentals
More of a reference book than a read-through book. Goes through the Java core API. Already knew most of it
Senior Engineers Reduce Risk
The impact of senior engineers goes beyond code.
Kalman filters are a simple but powerful technique for determining the most likely current state of an object in motion.
What Tech Stacks are Indie Hackers Using for Their Apps, and Why?
Descriptions of tech stacks and justifications for them at small startups. Bottom line: build modularly with technology you're familiar with.
Transfer learning is powerful and underutilized.
Crafting Beautiful UX with API Requests
Developer experience matters internally and externally and there are some simple patterns to make it better.
Beyong Zero-Sum Thinking in the Game of Tech...and Life
Zero sum thinking in politics and economics is outdated and poisonous.
Bayesian Machine Learning
Intro to Bayesian Machine Learning
Game theory is the study of equilibria-based solutions.
Online Property Management Software vs. Excel
Use Online Property Management Software for Auditing and Intuition
Income and expenses: What property managers need to know
Summary of the relevant PM income and expense types, and who is responsible for each
Part 1: Intro
Part 3: Debits and Credits
Debits and Credits in PM Accounting
How to unit test machine learning code
Actual code examples for testing neural networks and ML algorithms yay
Tools for Remote Software Development and Pair Programming
Tools for Remote Software Development and Pair Programming
Software Estimation: Demystifying The Black Art
More of a reference book than a read-through book. Goes through a lot of software estimation techniques. Meat of the book was in the first section.