A Guide To Machine Learning Foundations of Task Management Software

Posted Leave a commentPosted in Machine Learning, SmartData Collective Exclusive, Software, task management, task management software

Task management applications are changing the way we manage teams. Here are some of the primary benefits of these task management applications: Task management tools improve team productivity Task management tools make sure that teams operate more efficiently Task management tools minimize worker stress Task management tools help with monitoring trends Machine learning is playing […]

Big Data Sets New Standards In Stream Processing For Emerging Markets

Posted Leave a commentPosted in Big Data, data standards, emerging markets, Privacy, SmartData Collective Exclusive, stream processing

With today’s technology, there’s an increasing demand for stream processing. Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. […]

How Big Data Makes Us Rethink The Design Of Magnetic Devices

Posted Leave a commentPosted in Big Data, design, magnetic device, magnetic devices, magnetics, SmartData Collective Exclusive

One of the most fascinating things about big data is its ability to optimize the design of products that have pre-dated digital technology by centuries. One of the most interesting examples is with magnets. Magnets are ancient devices. They are so old, that the history of their discovery has been lost in legend. It is […]

Hyperparameter Tuning with MLflow, Apache Spark MLlib and Hyperopt

Posted Leave a commentPosted in Apache Spark, AutoML, Data Science, Databricks Runtime 5.4 ML, Deep Learning, Ecosystem, Engineering Blog, Hyperopt, Hyperparameter Tuning, Machine Learning, MLflow, MLlib

Hyperparameter tuning is a common technique to optimize machine learning models based on hyperparameters, or configurations that are not learned during model training.  Tuning these configurations can dramatically improve model performance. However, hyperparameter tuning can be computationally expensive, slow, and unintuitive even for experts. Databricks Runtime 5.4 and 5.4 ML (Azure | AWS) introduce new […]

Announcing the MLflow 1.0 Release

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Ecosystem, Engineering Blog, Lifecycle, Machine Learning, MLflow, Model Management, Product

MLflow is an open source platform to help manage the complete machine learning lifecycle. With MLflow, data scientists can track and share experiments locally (on a laptop) or remotely (in the cloud), package and share models across frameworks, and deploy models virtually anywhere. Today we are excited to announce the release of MLflow 1.0. Since […]

What Skills Do You Need to Become a Blockchain Engineer?

Posted Leave a commentPosted in Blockchain

In its latest report, Gartner predicts that by 2021, almost 90% of the current enterprises will require to replace blockchain platforms in order to stay relevant, competitive, protected and not become redundant. With blockchain becoming the go-to technology for most industries, the popularity keeps increasing. Businesses from almost every country, major organizations and even the […]

Enhanced Hyperparameter Tuning and Optimized AWS Storage with Databricks Runtime 5.4 ML

Posted Leave a commentPosted in Announcements, AutoML, Company Blog, Data Science, Databricks Runtime 5.4 ML, Deep Learning, Ecosystem, Engineering Blog, Hyperopt, Hyperparameter Tuning, Machine Learning, MLflow, MLlib, Platform, Product

We are excited to announce the release of Databricks Runtime 5.4 ML (Azure | AWS). This release includes two Public Preview features to improve data science productivity, optimized storage in AWS for developing distributed applications, and a number of Python library upgrades. To get started, you simply select the Databricks Runtime 5.4 ML from the […]

Protecting the Securities Market with Predictive Fraud Detection

Posted Leave a commentPosted in Company Blog, Customers, Financial Fraud, Financial Markets, Financial Services, FINRA, Fraud, Fraud Detection, Securities Market

FINRA (Financial Industry Regulatory Authority), a regulatory body charged with protecting the U.S. securities market, spoke at the Spark + AI Summit on how they use Databricks Unified Analytics Platform to analyze up to a 100 billion stock market events per day for fraud detection and prevention. This is a summary of their story from Summit. […]