AI Feynman 2.0: Learning Regression Equations From Data

A NEW AI LIBRARY FROM MAX TEGMARK’S LAB AT MIT Let’s kick the tires on a brand new library Image by Gerd Altmann from Pixabay (CC0) Table of Contents 1. Introduction2. Code3. Their Example4. Our Own Easy Example5. Symbolic Regression on Noisy Data 1. A New Symbolic Regression Library I recently saw a post on … Read more AI Feynman 2.0: Learning Regression Equations From Data

Not just compliance: reimagining DLP for today’s cloud-centric worldNot just compliance: reimagining DLP for today’s cloud-centric worldProduct Manager, Google CloudHead of Solutions Strategy

As the name suggests, data loss prevention (DLP) technology is designed to help organizations monitor, detect, and ultimately prevent attacks and other events that can result in data exfiltration and loss. The DLP technology ecosystem—covering network DLP, endpoint DLP, and data discovery DLP—has a long history, going back nearly 20 years, and with data losses … Read more Not just compliance: reimagining DLP for today’s cloud-centric worldNot just compliance: reimagining DLP for today’s cloud-centric worldProduct Manager, Google CloudHead of Solutions Strategy

An Intuitive Explanation of the Bayesian Information Criterion

Going back to our example, you could imagine a model that has as many clusters as there are data points. See, no outliers! But that wouldn’t be a very useful model. All models are wrong, but some are useful. We have to balance the maximum likelihood of our model, L, against the number of model … Read more An Intuitive Explanation of the Bayesian Information Criterion

11 best practices for operational efficiency and cost reduction with Google Cloud11 best practices for operational efficiency and cost reduction with Google CloudHead of Solutions Engineering Center of Excellence

As businesses consider the road ahead, many are finding they need to make tough decisions about what projects to prioritize and how to allocate resources. For many, the impact of COVID-19 has brought the benefits and limitations of their IT environment into focus. As these businesses plan their way forward, many will need to consider … Read more 11 best practices for operational efficiency and cost reduction with Google Cloud11 best practices for operational efficiency and cost reduction with Google CloudHead of Solutions Engineering Center of Excellence

Building a genomics analysis architecture with Hail, BigQuery, and DataprocBuilding a genomics analysis architecture with Hail, BigQuery, and DataprocProduct Manager

Here’s more detail on each of the components. Landing zone The landing zone, also referred to by some customers as their “raw zone,” is where data is ingested in its native format without transformations or making any assumptions about what questions might be asked of it later.  For the most part, Cloud Storage is well-suited … Read more Building a genomics analysis architecture with Hail, BigQuery, and DataprocBuilding a genomics analysis architecture with Hail, BigQuery, and DataprocProduct Manager

Presto optional component now available on DataprocPresto optional component now available on DataprocDeveloper AdvocateDeveloper Programs Engineer

Presto is an open source, distributed SQL query engine for running interactive analytics queries against data sources of many types. We are pleased to announce the GA release of the Presto optional component for Dataproc, our fully managed cloud service for running data processing software from the open source ecosystem. This new optional component brings … Read more Presto optional component now available on DataprocPresto optional component now available on DataprocDeveloper AdvocateDeveloper Programs Engineer

Genomics analysis with Hail, BigQuery, and DataprocGenomics analysis with Hail, BigQuery, and DataprocProduct Manager

At Google Cloud, we work with organizations performing large-scale research projects. There are a few solutions we recommend to do this type of work, so that researchers can focus on what they do best—power novel treatments, personalized medicine, and advancements in pharmaceuticals. (Find more details about creating a genomics data analysis architecture in this post.) … Read more Genomics analysis with Hail, BigQuery, and DataprocGenomics analysis with Hail, BigQuery, and DataprocProduct Manager

Data science at NASA

Editor’s note: The Towards Data Science podcast’s “Climbing the Data Science Ladder” series is hosted by Jeremie Harris. Jeremie helps run a data science mentorship startup called SharpestMinds. You can listen to the podcast below: Machine learning isn’t rocket science, unless you’re doing it at NASA. And if you happen to be doing data science … Read more Data science at NASA

Tip (4), Variable Explorer for both R and Python in RStudio

In recent past, frequent usage of both Rand Python by Data Scientists are considerably increasing. RStudio is preferred IDE for most of R users, though, there are Editors and Notebooks which serve for both languages, yet, switching between them is not easy. Especially for those who got used to RStudio “Environment” tab for exploring objects in current R sessions; though, writing/execution of  Related Favorite

Build, distribute, and deploy application updates to Azure virtual machine scale sets

As the needs of your business grow, and you deploy business-critical applications at cloud scale, the complexity and administrative overhead of managing those applications can increase substantially. To help reduce this management overhead, Azure continues to invest in new capabilities that make it easier to build and distribute application updates across distributed cloud environments. We … Read more Build, distribute, and deploy application updates to Azure virtual machine scale sets

Azure Firewall Manager is now generally available

Azure Firewall Manager is now generally available and includes Azure Firewall Policy, Azure Firewall in a Virtual WAN Hub (Secure Virtual Hub), and Hub Virtual Network. In addition, we are introducing several new capabilities to Firewall Manager and Firewall Policy to align with the standalone Azure Firewall configuration capabilities. Key features in this release include: … Read more Azure Firewall Manager is now generally available

Gradient Descent animation: 1. Simple linear Regression

This is the first part of a series of articles on how to create animated plots visualizing gradient descent. The Gradient Descent method is one of the most widely used parameter optimization algorithms in machine learning today. Python’s celluloid-module enables us to create vivid animations of model parameters and costs during gradient descent. In this … Read more Gradient Descent animation: 1. Simple linear Regression

Is your website leaking sensitive information?

There has been a lack of attention for XSLeaks (cross-site leaks) which result in the leaking of user information source Most developers are familiar and aware of the security vulnerabilities XSS (Cross-site scripting), CSRF (Cross-site request forgery) or SQL Injection, but there has been a lack of attention for XSLeaks (cross-site leaks) which can result … Read more Is your website leaking sensitive information?

The Coronavirus vs Voice Technology in Asia

How COVID-19 has accelerated a “voice technology moment” that could change communication forever Tokyo. Photo by author. The coronavirus has led to all kinds of innovation: Korea invented drive-through testing, Lithuania invented 3D-printed hands-free door handles, and at this point, nearly everyone has shifted their meetings and social events to a VoIP solution like Zoom. … Read more The Coronavirus vs Voice Technology in Asia

Getting Started with GANs Using PyTorch

We will see the ability of GAN to generate new images which makes GANs look a little bit “magic”, at first sight. A generative adversarial network (GAN) is a class of machine learning frameworks conceived in 2014 by Ian Goodfellow and his colleagues. Two neural networks (Generator and Discriminator) compete with each other like in … Read more Getting Started with GANs Using PyTorch

Activations, Convolutions, and Pooling — Part 4

Pooling Mechanisms Deep Learning at FAU. Image under CC BY 4.0 from the Deep Learning Lecture These are the lecture notes for FAU’s YouTube Lecture “Deep Learning”. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created … Read more Activations, Convolutions, and Pooling — Part 4

10 Reasons Why You Need Reliable Data Quality

Good, Bad Or Ugly In this data-driven age, organizations are looking to leverage data to enhance business efficiency and effectiveness. The decision on all levels are made with the use of BI and Advanced Analytics tools, better the data better outputs those tools provide and that leads to the creation of opportunities, generating more revenue … Read more 10 Reasons Why You Need Reliable Data Quality

Open-Source Authorship of Data Science in Education Using R

[This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Joshua M. Rosenberg, Ph.D., is Assistant Professor of STEM Education at theUniversity … Read more Open-Source Authorship of Data Science in Education Using R

Using Pyomo from R through the magic of Reticulate

Pyomo is a python based open-source package for modeling optimization problems. It makes it easy to represent optimization problems and can send it to different solvers (both open-source and commercial) to solve the problem and return the results in python. The advantage of pyomo compared to commercial software such as GAMS and AMPL is the … Read more Using Pyomo from R through the magic of Reticulate

Announcing Public Package Manager and v1.1.6

[This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Today we are excited to release version 1.1.6 of RStudio Package Manager … Read more Announcing Public Package Manager and v1.1.6

Rethinking Continuous Integration for Data Science

Software Engineering for Data Science A widely used practice in software engineering deserves its own flavor in our field Photo by Yancy Min on Unsplash As Data Science and Machine learning get wider industry adoption, practitioners realize that deploying data products comes with a high (and often unexpected) maintenance cost. As Sculley and co-authors argue … Read more Rethinking Continuous Integration for Data Science

Roadmap to Machine Learning: Key Concepts Explained

What if our memory was a storage device? How much easier the learning process would be. But the reality is to become an excellent professional in something you need to go through the thorny path. You learn, you forget, you make mistakes, you learn again, absorb new things, and thus you form a picture of … Read more Roadmap to Machine Learning: Key Concepts Explained

10 Minutes to Building a Fully-Connected Binary Image Classifier in TensorFlow

Photo by Waranont (Joe) on Unsplash How to build a binary image classifier using fully-connected layers in TensorFlow/Keras This is a short introduction to computer vision — namely, how to build a binary image classifier using only fully-connected layers in TensorFlow/Keras, geared mainly towards new users. This easy-to-follow tutorial is broken down into 3 sections: … Read more 10 Minutes to Building a Fully-Connected Binary Image Classifier in TensorFlow

beta: Evidence-based Software Engineering – book

[This article was first published on The Shape of Code » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. My book, Evidence-based software engineering: based on the … Read more beta: Evidence-based Software Engineering – book

K Nearest Neighbors by hand: A Computer Science exercise for the Data Scientist

Opening the “black box” and understanding the algorithm within Data scientists sometimes talk about a “black box” approach to data science. That is, when you understand the use cases for different machine learning algorithms and how to plug in the data without understanding how the algorithm works beneath the surface. But the algorithms are just … Read more K Nearest Neighbors by hand: A Computer Science exercise for the Data Scientist

New IT Cost Assessment program: Unlock value to reinvest for growthNew IT Cost Assessment program: Unlock value to reinvest for growthVP, Solutions Engineering

If you’re in IT, chances are you’re under pressure to prioritize investments and optimize costs in response to the current economic climate. According to a recent survey of our customers1, that situation describes 84% of IT decision makers. Likewise, Forrester Research has said CIOs could face a minimum of 5% budget cuts in 20202, and … Read more New IT Cost Assessment program: Unlock value to reinvest for growthNew IT Cost Assessment program: Unlock value to reinvest for growthVP, Solutions Engineering

Measuring Financial Risk: A Step-by-Step Guide

To calculate our own VaR and ES, we’ll use data for the Wilshire 5000, a stock market index widely considered to be the broadest measure of U.S. stock prices. We can use quantmod to import our data from FRED, the Federal Reserve Economic Database. We’ll also use ggplot2 to visualize our data. Let’s load our … Read more Measuring Financial Risk: A Step-by-Step Guide

How to create Latex tables directly from Python code

Copying tables of results from the console into a Latex report can be tedious and error fraught — so why not automate it? Making tables should be simple and elegant (Photo by Roman Bozhko on Unsplash). Creating tables of results plays a major part in communicating the outcomes of experiments in data science. Various solutions … Read more How to create Latex tables directly from Python code

Serverless BERT with HuggingFace and AWS Lambda

A typical transformers model consists of a pytorch_model.bin, config.json, special_tokens_map.json, tokenizer_config.json, and vocab.txt. The pytorch_model.bin has already been extracted and uploaded to S3. We are going to add config.json, special_tokens_map.json, tokenizer_config.json, and vocab.txt directly into our Lambda function because they are only a few KB in size. Therefore we create a model directory in our … Read more Serverless BERT with HuggingFace and AWS Lambda

Machine Learning Basics: Multiple Linear Regression

Learn to Implement Multiple Linear Regression with Python programming. In the previous story, I had given a brief of Linear Regression and showed how to perform Simple Linear Regression. In Simple Linear Regression, we had one dependent variable (y) and one independent variable (x). What if the marks of the student depended on two or … Read more Machine Learning Basics: Multiple Linear Regression

Deploying Python script to Docker container and connect to external SQL Server(in 10 minutes)

Finally we want to build and run the image. #Build the imagedocker build -t my-app .#Run itdocker run my-app#Find container namedocker ps –last 1#Check logsdocker logs <container name> If you want to explore the container and run the script manually then modify last line of the Dockerfile, build and run again: #CMD [“python”,”-i”,”main.py”]CMD tail -f … Read more Deploying Python script to Docker container and connect to external SQL Server(in 10 minutes)

How Can AI Boost Call Center Moral?

What if we used these technologies to actually make call center agents’ lives better? I don’t mean coaching them to do a better job. “Feedback overload” is already a recognized problem in call centers. I mean helping them cope with the fact that their job is emotionally draining. Remember how frustrating it was the last … Read more How Can AI Boost Call Center Moral?

Build your own deep learning classification model in Keras

Step #6: Create our model In this task we will build a classification convolutional neural network from scratch and train it to recognize the 20 target classes in the Pascal Voc dataset. Our Model architecture will be based on the popular VGG-16 architecture. This is a CNN with a total of 13 convolutional layers (cfr. … Read more Build your own deep learning classification model in Keras

Anything2Vec: Mapping Reddit into Vector Spaces

Generalizing Word2Vec away from word embeddings “Subreddit Embedding” and the 100 closest subreddits to /r/nba A common problem in ML, natural language processing (NLP), and AI at large surrounds representing objects in a way computers can process. And since computers understand numbers — which we have a common language for comparing, combining and manipulating — … Read more Anything2Vec: Mapping Reddit into Vector Spaces

Azure Cost Management + Billing updates – June 2020

Whether you’re a new student, thriving startup, or the largest enterprise, you have financial constraints and you need to know what you’re spending, where, and how to plan for the future. Nobody wants a surprise when it comes to the bill, and this is where Azure Cost Management + Billing comes in. We’re always looking … Read more Azure Cost Management + Billing updates – June 2020

New Azure Firewall features in Q2 CY2020

We are pleased to announce several new Azure Firewall features that allow your organization to improve security, have more customization, and manage rules more easily. These new capabilities were added based on your top feedback: Custom DNS support now in preview. DNS Proxy support now in preview. FQDN filtering in network rules now in preview. IP … Read more New Azure Firewall features in Q2 CY2020

Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models

Forecasting the future has always been one of man’s biggest desires and many approaches have been tried over the centuries. In this post we will look at a simple statistical method for time series analysis, called AR for Autoregressive Model. We will use this method to predict future sales data and will rebuild it to … Read more Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models

[Paper Summary] Distilling the Knowledge in a Neural Network

Photo by Aw Creative on Unsplash The authors start the paper with a very interesting analogy to explain the notion that the requirements for the training & inference could be very different. The analogy given is that of a larva and its adult form and the fact the requirements of nourishments for the two forms … Read more [Paper Summary] Distilling the Knowledge in a Neural Network

The Correct Way to Measure Inference Time of Deep Neural Networks

The network latency is one of the more crucial aspects of deploying a deep network into a production environment. Most real-world applications require blazingly fast inference time, varying anywhere from a few milliseconds to one second. But the task of correctly and meaningfully measuring the inference time, or latency, of a neural network, requires profound … Read more The Correct Way to Measure Inference Time of Deep Neural Networks

How to scrape ANY website with python and beautiful soup

Now you don’t need to know how HTML/CSS works (although, it can be really helpful if you do). The only thing that’s important to know is that you can think of every HTML tag as an object. These HTML tags have attributes that you can query, and each one is different. Each line of code … Read more How to scrape ANY website with python and beautiful soup