Coronavirus Fighting COVID-19 with Data and AI: A Review of Active Research Groups and Datasets The economy has come to a halt; people are quarantined; work is stagnating; and governments fear the public health crisis this could turn into. The deadly coronavirus (SARS-CoV-2, or COVID-19
Announcement Introducing Paperspace + Hugging Face 🤗 We're excited to announce a new collaboration with Hugging Face to provide state-of-the-art NLP tools to the community. Gradient + Hugging FaceThe new Transformers container makes it simple to deploy cutting-edge
Data Science Introduction to Naive Bayes: A Probability-Based Classification Algorithm Imagine this: an electricity operator would like to supply specific units of electric current to various factory divisions based on their past trends of power consumption. To simplify the process,
Coronavirus Fighting Coronavirus With AI, Part 1: Improving Testing with Deep Learning and Computer Vision This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.
Series: Ensemble Methods Gradient Boosting In Classification: Not a Black Box Anymore! Machine learning algorithms require more than just fitting models and making predictions to improve accuracy. Most winning models in the industry or in competitions have been using Ensemble Techniques or
Machine Learning How To Implement Support Vector Machine With Scikit-Learn In this tutorial we'll cover: An introduction to the support vector machine algorithmImplementing SVM using Python and SklearnSo, let's get started! Bring this project to life Run on gradientIntroduction to
Research Neural Architecture Search Part 1: An Overview The hyperparameter optimization problem has been solved in many different ways for classical machine learning algorithms. Some examples include the use of grid search, random search, Bayesian optimization, meta-learning, and
Data Science Implementing The Levenshtein Distance for Word Autocompletion and Autocorrection The Levenshtein distance is a text similarity measure that compares two words and returns a numeric value representing the distance between them. The distance reflects the total number of single-character
Interviews The Future of Data Privacy As many people know, data access is one of the limitations to applications of powerful supervised learning models in critical areas such as healthcare. Without strategies to ensure privacy, that
Data Science Measuring Text Similarity Using the Levenshtein Distance In word processing or text chat applications, it's common that users make some unintended spelling mistakes. It could be as simple as writing "helo" (single "l") rather than "hello". Luckily,
Interviews Cerebral Sandwiches and Connectomics of the Brain Casimir Wierzynski, a senior director in Intel's AI products group, talked to me about his work in connectomics with "salami slicers" for the brain that are making it possible to
Data Science Anomaly Detection Using Isolation Forest in Python From bank fraud to preventative machine maintenance, anomaly detection is an incredibly useful and common application of machine learning. The isolation forest algorithm is a simple yet powerful choice to
News How AI And Deep Learning Are Shaping Education: An Interview With Terry Sejnowski Among Terry Sejnowski’s many interests has been a focus on education, specifically how we can use what we know about learning in the brain to improve education. A little
Series: Ensemble Methods A Guide to AdaBoost: Boosting To Save The Day Today, machine learning is the premise of big innovations and promises to continue enabling companies to make the best decisions through accurate predictions. But what happens when the error susceptibility
News Do Machines Dream? An Interview With Terry Sejnowski on Boltzmann Machines and The Brain Terry Sejnowski is one of the pioneers of deep learning who, together with Geoffrey Hinton, created Boltzmann machines: a deep learning network that has remarkable similarities to learning in the
Series: Ensemble Methods A Guide To Random Forests: Consolidating Decision Trees The Random Forest algorithm is one of the most popular machine learning algorithms that is used for both classification and regression. The ability to perform both tasks makes it unique,
Series: Ensemble Methods An Introduction to Decision Trees Decision Trees are the foundation for many classical machine learning algorithms like Random Forests, Bagging, and Boosted Decision Trees. They were first proposed by Leo Breiman, a statistician at the
News The Future of ML: Unsupervised Learning, Reinforcement Learning, or Something Else? Yoshua and Samy Bengio, Yann Lecun, Rich Sutton and Sergey Levine talk about the future of machine learning and how unsupervised learning methods will likely get us to human-level intelligence in machines.
Keras Working With The Lambda Layer in Keras In this tutorial we'll cover how to use the Lambda layer in Keras to build, save, and load models which perform custom operations on your data.
Series: GauGAN Understanding GauGAN Part 4: Debugging Training & Deciding If GauGAN Is Right For You In this post we cover how to tackle common training issues that may arise with GauGAN. We conclude with advice on whether GauGAN will fit your business needs or not.
News Climate Change, China and AI Climate change and competition with China are the two things that top my list of the most important trends in machine learning. I had the opportunity to talk with key people in both of those realms in recent months for the Eye on AI podcast.
Series: GauGAN Understanding GauGAN Part 3: Model Evaluation Techniques Hi folks, welcome to the third part of the GauGAN series. In the last two parts we've covered the components and losses of GauGAN, and how to set up custom
Deep Learning Image Compression Using Autoencoders in Keras Autoencoders are a deep learning model for transforming data from a high-dimensional space to a lower-dimensional space. They work by encoding the data, whatever its size, to a 1-D vector.
Gradient Paperspace Gradient vs Amazon SageMaker Paperspace Gradient and Amazon SageMaker make it easier to take machine learning models from research to production. Learn about the differences between the two platforms!
Computer Vision Image Captioning With AI One application that has really caught the attention of many folks in the space of artificial intelligence is image captioning. If you think about it, there is seemingly no way
