Binance Tai-Chi Document

How to Implement an ERC721 Market


What does an executive do

Job #2: Allocate scarce resources.

Job #3: Craft vision.

Job #4: Break ties.

Job #5: Curate Culture.

Job #6: Advocate, explain, and be held accountable.

Gems from Richard Hamming

On Great Thoughts Fridays:

Friday afternoons for years — great thoughts only — means that I committed 10% of my time trying to understand the bigger problems in the field, i.e. what was and what was not important. I found in the early days I had believed `this’ and yet had spent all week marching in `that’ direction. It was kind of foolish. If I really believe the action is over there, why do I march in this direction? I either had to change my goal or change what I did. So I changed something I did and I marched in the direction I thought was important.

I think this is a great idea. In addition to 20% time (where a lack of productivity is almost the primary short term goal), I would love to devote some portion of my schedule to thinking about what is and isn’t important.

Also, the format this is done is great > take up key quotes and critique slightly

Opinionated guides

How To Identify A Problem Worth Solving

  1. Intensity — how painful is this problem to your customer?
  2. Willingness to pay — how much is your customer willing to pay to make this problem go away?

How to Identify a Future Billionaire, According to a Legendary Investor

First of all, Jason says that he doesn’t pay too much attention to the business ideas he’s presented with. The only thing he’s looking for is personality.

“You have to bet on people. Because even an entrepreneur who maybe builds the wrong product in the wrong market, they’ll be smart enough and indefatigable enough, resilient enough to realize ‘oh, this didn’t work, let’s make a couple little adjustments, maybe a full pivot.’ And they’ll figure it out.”

All about product careers

  1. The Start-up of You: Adapt to the Future, Invest in Yourself, and Transform Your Career
  2. Cracking the PM Interview: How to Land a Product Manager Job in Technology
  3. Mindset — Updated Edition: Changing The Way You think To Fulfil Your Potential
  4. Designing Your Life: Build the Perfect Career, Step by Step
  5. The First 90 Days, Updated and Expanded: Proven Strategies for Getting Up to Speed Faster and Smarter

We Analyzed 180K Business Proposals (You’ll Never Guess What We Found!)

However, our report has shown that you should consider the following elements when creating your proposal:

  • Use a template
  • Include a proposal cover
  • Use live chat
  • Send an online version of the proposal (don’t print)
  • Make it 6 pages long
  • Cram the word investment into the title
  • Send it within 24 hours from contact with the client


EIB Group adopts Climate Bank Roadmap and approves € 400 million for COVAX initiative to ensure global access to COVID-19 vaccine, part of € 7.8 billion for COVID-19 support, transport, water and cities.

Will have to look at it’s criticisms and praiess


ML Infrastructure Tools for Production (Part 1)

Full Stack Data Science: The Next Gen of Data Scientist Cohort

  1. Production ML/Data Pipelines: If you can get hands-on experience with Apache Airflow, a standard open-source job orchestration tool for creating data and machine learning pipelines. This is currently used in the industry so, it’s recommended to learn and get some projects around it.
  2. DevOps/Cloud: DevOps is very much neglected by most of the data science aspirants. If you don’t have an infrastructure, how would you build ML pipelines? It’s not as easy as we do in the coursework to build notebooks or code that run on your local machine. The code that you write should be scalable across infrastructure that you or other folks might create on your team. Many companies might not have the ML infrastructure already laid out and might be looking for someone to start with. Getting familiar with Docker, Kubernetes, and building ML applications with frameworks like Flask should be your standard practice even during your coursework. I love Docker as it’s scalable and you can build infrastructure images and replicate the same things on servers/cloud on Kubernetes clusters.
  3. Databases: Knowing databases and query languages is a must. SQL is very much neglected, but It’s still the industry standard, be it on any cloud platform or databases. Start practicing complex SQLs on leetcode, which is gonna help you with some part of coding interviews in DS profiles as you will be responsible for bringing in data from warehouses with on-the-go preprocessing, which will ease up your job on preprocessing before running ML models. Most of the feature engineering can be done on-the-go while getting the data to your models with SQL, which is an aspect many people neglect.
  4. Programming Languages: The recommended programming languages for data science are Python, R, Scala, and Java. Knowing anyone of them is fine and can do the trick. For ML kind of roles, there’s going to be live coding rounds in the interview process so you need to practice wherever you are comfortable — Leetcode, Hackerrank, or anything you prefer.


Foundations of Software Engineering

Architecture playbook

Learn Ruby on Rails by Creating a Friends List App

Solidify Your React Skills by Building 15 Projects — Free Course

  • Birthday Reminder
  • Tours Page
  • Reviews Page
  • Accordion
  • Menu
  • Tabs Portfolio
  • Slider
  • Lorem Ipsum Generator
  • Color Generator
  • Grocery List
  • Navbar
  • Sidebar and Model
  • Stripe Menu
  • Shopping Cart
  • Cocktail Page

Learn Microsoft Excel — Full Video Course

  • navigate through a spreadsheet,
  • create formulas to solve problems,
  • create charts and graphs,
  • understand relative vs absolute references,
  • import and export data,
  • implement VLOOKUP,
  • use pivot tables,
  • split and concatenate text,
  • and more.

What is Metaprogramming in JavaScript? In English, please.

  • Generate code
  • Manipulate language constructs at the run time. This phenomenon is known as Reflective Metaprogramming or Reflection.


Beyond Good and Evil: Nietzsche on Love, Perseverance, and true mark of greatness

It is not the strength, but the duration of great sentiments that makes great men.

A man of genius is unbearable, unless he possess at least two things besides: gratitude and purity.

He who fights with monsters should be careful lest he thereby become a monster. And if thou gaze long into an abyss, the abyss will also gaze into thee.

What is done out of love always takes place beyond good and evil.


Misinformation in Elections, Facebook accountability


Unbundling Harvard: How The Traditional University Is Being Disrupted

Universities have had so much power for too long. Interesting how they’ve also unwittingly illustrated the core business of universities. Everything else is peripheral

How to build your strategy so it has its own network effect

When considering the strategy, there are three ways organisations can invest in their network effect. These are:

  1. Grow one part of the network: increasing the value it contributes, both as a standalone entity and through its connections to the whole.
  2. Create/strengthen connections within the network: increasing the leverage of each area within the portfolio.
  3. Add new participants into the network: which extend the scope of the entire network and creates more opportunities to do 1) and 2).


Ribbon: instant user interviews

Baller to-do: impact matrix

Funkwhale music sharing

v-one monetisable no code apps

ever curious