Sat.Feb 09, 2019 - Fri.Feb 15, 2019

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A Data Scientist’s relationship with building Predictive Models

Dataconomy

If you’re a Data Scientist, you’ve likely spent months earnestly developing and then deploying a single predictive model. The truth is that once your model is built – that’s only half the battle won. A quarter of a Data Scientist’s working life often goes something like this: You met with. The post A Data Scientist’s relationship with building Predictive Models appeared first on Dataconomy.

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Typical Data Scientist 2019

Data Science 101

The profile of a data scientist is changing slightly as the profession becomes more solidified. Data Science 365 conducts a study to determine some of the characteristics of a “typical data scientist.” The below infographic covers a wealth of information from programming languages used to educational backgrounds to locations. It is definitely worth looking at to understand the attributes of a data scientist in 2019.

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Predict Your Relationship Future with Machine Learning

DataRobot Blog

by Jen Underwood. In the spirit of Valentine’s Day, let’s explore a fun little Relationship App quiz that forecasts how long your relationship will last. Data from a Stanford University study, How Couples. Read More.

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How to use magnitude with keras

Depends on the Definition

This time we have a look into the magnitude library, a feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Understanding building blocks of ULMFIT

ML Review

Understanding building blocks of ULMFIT Last week I had the time to tackle a Kaggle NLP competition: Quora Insincere Questions Classification. As it’s easy to understand from the name, the task is to identify sincere and insincere questions given the question text. In short it’s a binary classification problem. I recently completed Fast.ai Part 1 (2019).

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Help set the standards for a Data Scientist

Data Science 101

The field of data science is moving fast. People are claiming to be data scientists; yet the knowledge, experience, and backgrounds of those people can be very different. Different is not bad. However, there a little standards around what exactly a data scientist is. Sticking with this week’s theme of “What is a Data Scientist”, an organization titled, Initiative for Analytics and Data Science Standards (IADSS) has kicked-off a research study at global scale.

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Can You Find The Bug in This Code?

Victor Zhou

Here’s a bit of Javascript that prints “Hello World!” on two lines: ( function ( ) { ( function ( ) { console. log ( 'Hello' ) } ) ( ) ( function ( ) { console. log ( 'World!' ) } ) ( ) } ) ( ) …except it fails with a runtime error. Can you spot the bug without running the code? Scroll down for a hint. Hint Here’s the text of the error: TypeError: (intermediate value)(.) is not a function What’s going on?

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