Medallion

Why machine learning models fail in finance: noisy data, scarce samples, and chaotic markets make prediction nearly impossible.

Why ML Can Predict the Weather, but Not Financial Markets

The OLTP/OLAP split no longer fits how developers build today. Postgres and the lakehouse are now used side-by-side – but stitched together with brittle 

Postgres and the Lakehouse Are Becoming One System — Here’s What Comes Next

Check out the Startup of The Year 2024 winners in the Healthcare industry!

Startups of The Year 2024 Winners: Healthcare

Trying to create a single AI that can answer all business analytics questions is challenging, if not impossible.

Text-to-SQL Was Supposed to Be AI’s Killer App. It’s Not.

mlops with databricks, mlflow, model registry, experiment tracking, feature store, machin learning pipeline, tutorial, machine learning and data engineering, 

Let's Build an MLOps Pipeline With Databricks and Spark - Part 1

A Modern Datalake is one-half Data Warehouse and one- half Data Lake. It uses object storage in terms of scalability and performance.

The Architect’s Guide to A Modern Datalake Reference Architecture

What if history's great men and women like Ceasar, Cleopatra, Marie Curie or Jesus were alive today? I imagined them using social media to spread their message

If History Had Wi-Fi: Yesterday's Leaders, Today's Influencers

The spinner is very feeble, but so active that in twenty-four hours the silken globe attains the bulk of a hazel-nut and in a couple of weeks that of an apple.

THE PINE PROCESSIONARY: THE EGGS AND THE HATCHING

“And is it carbonic acid gas this time, too, that is driven out by the heat, as in the manufacture of lime?” asked Jules.

PLASTER OF PARIS

What are alternative data and how to use web scraping to build datasets for financial markets?

Utilizing Web Scraping and Alternative Data in Financial Markets

Find out how #oracles will create the foundation for interoperability and portability in the #metaverse in this panel from @OracleSummit!


Oracles Will Eventually Be the Bridge Between All Virtual Worlds

At the age of eighteen, Watt was sent to Glasgow, there to reside with his mother’s relatives, and to learn the trade of a mathematical-instrument maker.

Section I.—James Watt and his Inventions

"Because there is something out there, something which may make all the difference now. Warlock isn't an empty world."

UNWELCOME GUIDE

Talk of heat—or better not—on Xecho. 

Talk of heat—or better not—on Xecho

My father seems to have found no difficulty in living at peace with all men in and out of office at Lady Margaret's other foundation. 

CAMBRIDGE LIFE

And I remember her coming in late one evening with a note-book in her hand.


OUR PROGRESS FROM CAMDEN TOWN TO CREST HILL

The Count of Monte Cristo, Volume Two, Chapter 47: The Dappled Grays by Alexandre Dumas, père is part of HackerNoon’s Book Blog Post series. 

The Count of Monte Cristo, Illustrated: Chapter 47 - The Dappled Grays

Moby-Dick; or The Whale, Chapter 55: Of the Monstrous Pictures of Whales by Herman Melville is part of HackerNoon’s Book Blog Post series. 

Moby-Dick; or The Whale: Chapter 55 - Of the Monstrous Pictures of Whales 

Moby-Dick; or The Whale,  Chapter 34: The Cabin-Table by Herman Melville is part of HackerNoon’s Book Blog Post series. 

Moby-Dick; or The Whale: Chapter 34 - The Cabin-Table

Lambda architecture has 3 components, a) Speed layer, which is the streaming data layer or real time data layer, b) serving layer, which is the database layer, which is derived by aggregating data from speed layer, and c) batch layer, which is the set of computations which are perfomed on large sets of data, typically stored in a distributed file system. In this post i will be talking about how to implement the speed layer, by visualizing real time taxi data. Post that, the visualization will allow us to make some real time business decisions. Code for this article can be found here.

Lambda Architecture Speed Layer: Real-Time Visualization For Taxi [Part 1]

In this part i would be talking about the batch layer of the Lambda Architecture. Batch layer is computed by applying a function to the whole historical dataset, to answer some high level questions which cannot be answered by either speed layer or serving layer. The computations typically take hours or days to run, and the results are stored usually in a distributed file system (although this is not a requirement). For example, the queries that might need to be answered would range from the beginning of the dataset to now, in our case, till date how many cabs have served how many passengers, or what is the total distance driven by all the cabs. In this article i would try to answer questions like these based on the dataset that i have. The code for the article can be found here.

Lambda Architecture Batch Layer: Visualizing All Time Taxi Data [Part 3]

In this part i would be talking about the serving layer of the Lambda Architecture. Serving layer is derived either by performing computation on batch data to arrive at a view that is mid way from speed layer and batch layer 

Lambda Architecture Serving Layer: Real-Time Visualization For Taxi [Part 2]

Smart contracts have a lot of potential, even though they remain fairly limited in approach. Obtaining external data is impossible for a contract on its own. The future will inevitably involve decentralized oracles, which can serve many different purposes. 

More Competition is Good: Decentralized Blockchain Oracle Solutions

The first step is to understand what is data governance. Data Governance is an overloaded term and means different things to different people. It has been helpful to define Data Governance based on the outcomes it is supposed to deliver. In my case, Data Governance is any task required for:

MEDALLION

http://medallion.co

51-200 emps

Since n.d.

Medallion's Related Companies

Representing this company? Click here to claim and customize this page!

Reviews About Medallion

Medallion WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps

MEDALLION

http://medallion.co

51-200 emps

Since n.d.

Medallion's Related Companies

1944

225.4B

1963

102.8B

-1%

1982

82.2B

1806

73.7B

1802

33.4B

-1%

1980

10.4B

2015

1.8B

2015

2006

2016

-0.4%

1958

1848

1968

3%