Python developer salary July 2017

United States developers labor market analysis according to the results of July, 2017
07 August 2017   887
Python

Is a multi-paradigm programming language with easy-to-use syntax and many features including the support of the object-oriented and structured programming, created by Guido van Rossum and first released in 1991

We publish the analysis of the labor market of developers in the United States monthly. For Python developers there were 1,383 vacancies. The vacancy rates were distributed as follows. 

Salary Estimate Python July 2017  Python developer salary estimate 

The most of the developers are required in New York, NY; the least in Seattle, WA.

Number of vacancies in different cities Python July 2017  Number of Python developer vacancies in different cities

Among the companies that hire Python developers the leaders are: 

  • Smith & Keller
  • Jobspring Partners
  • Unlisted Company

Number of vacancies in different companies Python July 2017  Number of Python developer vacancies in different companies 

According to the experience required, the vacancies are distributed as follows.

Number of vacancies by experience level Python July 2017 Python developer vacancies by the experience level

The average salary and salary according to the level of experience were distributed as follows.

Average salary Python July 2017 Python developer average salary

The analysis was carried out by the Hype.codes portal method using the indeed.com data.

Students to Beat Google’s Machine-Learning Code

Student programmers' image classification algorithm successfully identifies the object in 93% of cases
13 August 2018   394

Developers-students from Fast.ai which organize free online computer training courses have created an image classification algorithm that successfully identifies the object in 93% of cases and copes with it faster than a similar Google algorithm with a similar configuration. The authors argue that "the creation of breakthrough technologies is not just for big companies". This is reported by MIT Technology Review.

When evaluating performance, the DAWNBench test was used, which calculates the speed and cost of teaching the neural network. During the Fast.ai experiment, the neural network was launched on 16 virtual AWS nodes, each contained 8 NVIDIA V100 graphics cards. This configuration achieved accuracy of 93% in 18 minutes, and the cost of machine time was estimated at $ 40. The result of Fast.ai is faster than the development of Google engineers by 40%, but the corporation uses its own clusters TPU Pod, so the comparison is not entirely objective.

The developers used the PyTorch Python library, as well as their own development - fastai. They were able to achieve this learning speed with the new method of cropping images from the ImageNet dataset: instead of square pictures, they began to use rectangular:

Fast AI
Fast AI

State-of-the-art results are not the exclusive domain of big companies. These are the obvious, dumb things that many researchers wouldn’t even think to do.
 

Jeremy Howard

Founder, Fast.AI

The authors tried to make the project accessible to everyone, so they simplified its infrastructure, refusing to use distributed computing systems and containers. To implement it, developers teamed up with engineers from the innovative division of the Pentagon (DIU) to release software to quickly create and support distributed models on AWS.