Terence Parr

Education · United States · 1-10 Employees

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Overview

Headquarters

United States

Revenue

<$5 Million

Industry

Education Training Business Services Research & Development
ZI Rank: 1
Signal Type
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ZI Rank
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About Terence Parr

Deep explanations of machine learning and related topics. Terence Parr is a tech lead at Google and until 2022 was a professor of data science / computer science at Univ. of San Francisco, where he was founding director of the MS in data science program in 2012. While he is best known for creating the ANTLR parser generator , Terence actually started out studying neural networks in grad school (1987). After 30 years of parsing, he's back to machine learning and really enjoys trying to explain complex topics deeply and in the simplest possible way. Follow @the_antlr_guy . One of the biggest challenges when writing code to implement deep learning networks is getting all of the tensor (matrix and vector) dimensions to line up properly, even when using predefined network layers. This article describes a new library called TensorSensor that clarifies exceptions by augmenting messages and visualizing Python code to indicate the shape of tensor variables. It works with JAX, Tensorflow, PyTorcRead more
Terence Parr's Social MediaPopular SearchesTerence ParrSIC Code 73,737NAICS Code 81,811Show more

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Company Name

Revenue

Number of Employees

Type

Funding

Founded In

Top Executive

Terence Parr

<$5M
1-10
Private
-
-
N/A
<$5M
11-50
Private
-
-
N/A
<$5M
1-10
Private
-
2018
<$5M
1-10
Private
-
-
N/A
<$5M
1-10
Private
-
2018
N/A
<$5M
1-10
Private
-
-
N/A
<$5M
1-10
Private
-
1950
NB
Nathan BrixiusChief Technology Officer
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Company Profile Activity

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Activity Insights

Terence Parr is experiencing very low activity levels compared to other companies in the Education sector.

What does this means?

Terence Parr is drawing exceptional interest within the Education industry, suggesting notable developments or strong market momentum, learn more about Terence Parr.

Terence Parr Tech Stack

A closer look at the technologies used by Terence Parr

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Frequently Asked Questions Regarding Terence Parr

What is Terence Parr's official website?
Terence Parr's official website is www.explained.ai
What is Terence Parr's Revenue?
Terence Parr's revenue is <$5 Million
What is Terence Parr's SIC code?
Terence Parr's SIC: 73,737
What is Terence Parr's NAICS code?
Terence Parr's NAICS: 81,811
How many employees does Terence Parr have?
Terence Parr has 1-10 employees
What industry does Terence Parr belong to?
Terence Parr is in the industry of: Education, Training, Business Services
What is Terence Parr competition?
Terence Parr top competitors include: DB Tsai, SimplyHeuristics, MemoAI, Bayesstat.com
What technology does Terence Parr use?
Some of the popular technologies that Terence Parr uses are: goo.gl, Google Font API, YouTube, Google Tag Manager
What does Terence Parr do?

Deep explanations of machine learning and related topics. Terence Parr is a tech lead at Google and until 2022 was a professor of data science / computer science at Univ. of San Francisco, where he was founding director of the MS in data science program in 2012. While he is best known for creating the ANTLR parser generator , Terence actually start... ed out studying neural networks in grad school (1987). After 30 years of parsing, he's back to machine learning and really enjoys trying to explain complex topics deeply and in the simplest possible way. Follow @the_antlr_guy . One of the biggest challenges when writing code to implement deep learning networks is getting all of the tensor (matrix and vector) dimensions to line up properly, even when using predefined network layers. This article describes a new library called TensorSensor that clarifies exceptions by augmenting messages and visualizing Python code to indicate the shape of tensor variables. It works with JAX, Tensorflow, PyTorch, and Numpy, as well as higher-level libraries like Keras and fastai. See also the TensorSensor implementation slides (PDF). Vanilla recurrent neural networks (RNNs) form the basis of more sophisticated models, such as LSTMs and GRUs. But, sometimes the neural network metaphor makes it less clear exactly what's going on. This articles explains RNNs without neural networks, stripping them down to its essencea series of vector transformations that result in embeddings for variable-length input vectors. I provide full PyTorch implementation notebooks that use just linear algebra and the autograd feature. Linear and logistic regression models are important because they are interpretable, fast, and form the basis of deep learning neural networks. Unfortunately, linear models have a tendency to chase outliers in the training data, which often leads to models that don't generalize well to new data. To produce models that generalize better, we all know to regularize our models. While there are lots of articles on the mechanics of ...Read More

What are Terence Parr social media links?
Terence Parr Twitter page
Is Terence Parr a public company?
Terence Parr is private company therefore does not currently have an official ticker symbol
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