Managing the Complete Machine Learning Lifecycle: On-Demand Webinar now available!

Posted Leave a commentPosted in Company Blog, Data Science, Ecosystem, Education, Machine Learning, Managed MLflow, MLflow, Model Management, Open Source, Product, Webinar

On March 7th, our team hosted a live webinar—Managing the Complete Machine Learning Lifecycle—with Andy Konwinski, Co-Founder and VP of Product at Databricks. In this webinar, we walked you through how MLflow, an open source framework for the complete Machine Learning lifecycle, helps solve for challenges around experiment tracking, reproducible projects and model deployment. Specifically, […]

Databricks Runtime 5.3 ML Now Generally Available

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Databricks Runtime 5.3 ML, Deep Learning, Ecosystem, Engineering Blog, Machine Learning, Product

We are excited to announce the general availability (GA) of Databricks Runtime for Machine Learning, as part of the release of Databricks Runtime 5.3 ML. Built on top of Databricks Runtime, Databricks Runtime ML is the optimized runtime for developing ML/DL applications in Databricks. It offers native integration with popular ML/DL frameworks, such as scikit-learn, […]

New Data Scientists Must Avoid these 4 Data Fallacies

Posted Leave a commentPosted in Best Practices, Big Data, data fallacies, Data Management, Data Science, Data Scientist, SmartData Collective Exclusive

There are countless applications of machine learning in 2019. The demand for machine learning developers is growing at a rapid pace. MIT recently announced that it is committing $1 billion to a new program to educate technology professionals about machine learning and artificial intelligence. New academic programs are likely to be launched to focus on […]

A Guide to Data Science, Python, and Advanced Analytics Talks at Spark + AI Summit 2019

Posted Leave a commentPosted in Advanced Analytics, Company Blog, Data Science, Education, python, Spark + AI Summit

With a tsunami of data, scale of computing resources available, and rapid development of easy-to-learn open source Machine Learning frameworks, data science and machine learning concepts are much easier to learn and implement today than they were a decade ago. As a result, across all industries, practitioners are using cutting-edge ML algorithms to solve tough […]

How A Shortage Of Data Scientists In The US Is Holding Back Big Data

Posted Leave a commentPosted in Big Data, Data Science, data scientist shortage, data scientists, shortage of data scientists, SmartData Collective Exclusive

The demand for big data is on the rise, but the industry is struggling to keep up with demand and develop the best possible algorithms. One of their biggest challenges is trying to recruit enough scientists to leverage big data to its full effectiveness. One survey showed that 1-in-3 data scientists working in the United […]

Managed MLflow on Databricks now in public preview

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Ecosystem, Engineering Blog, Machine Learning, Managed MLflow, MLflow, Platform, Product

Try this tutorial in Databricks Building production machine learning applications is challenging because there is no standard way to record experiments, ensure reproducible runs, and manage and deploy models. To address these challenges, last June we introduced MLflow, an open source platform to manage the ML lifecycle that works with any machine learning library and […]

Free mind mapping tools for data scientists to enhance structured thinking

Posted Leave a commentPosted in Data Science

The phrase “Data scientists” denote the persons who have a deep understanding of the relation between data and information. Their prime job is taking an immense volume of random data with an intention to manage and rearrange them using their competence of programming, mathematics, and statistics. To accomplish such responsible tasks, data scientists cannot but […]