Tag: python

Feed: AWS Government, Education, & Nonprofits Blog. Author: publicsector. The Intelligence Advanced Research Projects Activity (IARPA) Machine Intelligence from Cortical Networks (MICrONS) program seeks to revolutionize machine learning by better understanding the representations, transformations, and learning rules employed by the brain.We spoke with Dean Kleissas, Research Engineer working on the IARPA MICrONS Project at the Johns Hopkins University Applied Physics Laboratory (JHU/APL), and he shared more about the project, what makes it unique, and how the team leverages serverless technology. Could you tell us about the IARPA MICrONS Project? This project partners computer scientists, neuroscientists, biologists, and other researchers from ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Favio Vázquez. Outdated, inaccurate, or duplicated data won’t drive optimal data driven solutions. When data is inaccurate, leads are harder to track and nurture, and insights may be flawed. The data on which you base your big data strategy must be accurate, up-to-date, as complete as possible, and should not contain duplicate entries. Clean data results in better decisions. Cleaning data is the most time-consuming and least enjoyable data science task (until Optimus), but one of the most important ones. No one can start a data science, machine learning or data driven solution without being sure that the ... Read More

Feed: CDH – Cloudera Engineering Blog. Author: Cy Jervis. Cloudera Data Science Workbench provides freedom for data scientists. It gives them the flexibility to work with their favorite libraries using isolated environments with a container for each project. In JVM world such as Java or Scala, using your favorite packages on a Spark cluster is easy. Each application manages preferred packages using fat JARs, and it brings independent environments with the Spark cluster. Many data scientists prefer Python to Scala for data science, but it is not straightforward to use a Python library on a PySpark cluster without modification. To ... Read More

Feed: All - O'Reilly Media. Author: Ben Lorica. INL's Advanced Test Reactor (source: Idaho National Laboratory on Flickr) Learn how to build reinforcement learning applications by attending a tutorial on Ray at the Artificial Intelligence Conference in San Francisco, on September 17-20, 2017. Save 20% with the code BIGDATA20. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Robert Nishihara and Philipp Moritz, graduate students at UC Berkeley and members of ... Read More

Feed: All - O'Reilly Media. Author: Ben Lorica. Stockton Infinity Bridge (source: darren price on Flickr) There will back-to-back half-day tutorials on reinforcement learning at the upcoming Artificial Intelligence Conference in San Francisco: Building reinforcement learning applications with Ray and Introduction to reinforcement learning. As more companies begin to experiment with and deploy machine learning in different settings, it’s good to look ahead at what future systems might look like. Today, the typical sequence is to gather data, learn some underlying structure, and deploy an algorithm that systematically captures what you’ve learned. Gathering, preparing, and enriching the right data—particularly training ... Read More

Feed: All - O'Reilly Media. Author: Ben Lorica. Anatomy. (source: Pixabay) Learn how companies are using deep learning and AI by attending the Artificial Intelligence Conference in San Francisco, September 17-20, 2017. Save 20% with the code BIGDATA20. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Soumith Chintala, AI research engineer at Facebook. Among his many research projects, Chintala was part of the team behind DCGAN (Deep Convolutional Generative Adversarial ... Read More

Feed: All - O'Reilly Media. Author: Arthur Juliani. Image from page 206 of "Mazes and labyrinths; a general account of their history and developments" (1922). (source: Internet Archive on Flickr) Attention readers: We invite you to access the corresponding Python code and iPython notebooks for this article on GitHub. Reinforcement learning (RL) is about training agents to complete tasks. We typically think of this as being able to accomplish some goal. Take, for example, a robot we might want to train to open a door. Reinforcement learning can be used as a framework for teaching the robot to open the ... Read More

Feed: All - O'Reilly Media. Author: Manu Jeevan, Suresh Chelladurai. Road signs (source: Pixabay) The full Jupyter Notebook for this post can be accessed here. Although there are many deep learning frameworks, including TensorFlow, Keras, Torch, and Caffe, Apache MXNet in particular is gaining popularity due to its scalability across multiple GPUs. In this blog post, we'll tackle a computer vision problem: classifying German traffic signs using a convolutional neural network. The network takes a color photo containing a traffic sign image as input, and tries to identify the type of sign. The full notebook can be found here In ... Read More

Feed: Neo4j Graph Database. Author: Rachel Howard. By We analyzed the data and created a Gephi map of the 15,000 top users. One of the clusters we identified included journalists, the most prominent of whom was Washington Post reporter Because there was no budget, I had to use open source software and started with The original source code — the Python scripts and important routines for pulling this into Neo4j — is also still available on The key thing we learned in the research is that people are not disciplined about following the process of collecting data. Instead we typically ... Read More

Feed: Planet MySQL; Author: Shahriyar Rzayev; This post is about simple usage of mysqlx module i.e X Plugin with latest Connector/Python DMR.The version of Python Connector is 8.0.4. Installing: wget https://dev.mysql.com/get/Downloads/Connector-Python/mysql-connector-python-8.0.4-0.1.dmr.el7.x86_64.rpm sudo yum install mysql-connector-python-8.0.4-0.1.dmr.el7.x86_64.rpm Sample Python code: # Connecting to MySQL and working with a Session import mysqlx # Connect to a dedicated MySQL server session = mysqlx.get_session({ 'host': 'localhost', 'port': 33060, 'user': 'bakux', 'password': 'Baku12345', 'ssl-mode': mysqlx.SSLMode.DISABLED }) schema = session.get_schema('generated_columns_test') # Create 'my_collection' in schema schema.create_collection('my_collection') # Get 'my_collection' from schema collection = schema.get_collection('my_collection') assert(True == collection.exists_in_database()) # You can also add multiple documents at once collection.add({'_id': ... Read More