Brickster Spotlight: Meet Greg From Intern to Senior Software Engineer

Posted Leave a commentPosted in Company Blog, Culture, Data Science, Hyperopt, Hyperparameter Tuning, Machine Learning, MLflow, MLlib

At Databricks, we’re committed to learning and development at every level, so it’s important to our teams that we recruit and develop our next generation of Databricks leaders. Our interns are encouraged to live out one of our core values, “be an owner” and they play an integral role in developing our platform during their […]

Data Science Offers Fascinating New Scheduling Solutions

Posted Leave a commentPosted in Big Data, data, Data Science, scheduling, scheduling solutions, science, SmartData Collective Exclusive

At Smart Data Collective, we often emphasize the biggest trends in the field of big data. We have talked extensively about the application of big data in everything from large-scale marketing to criminal justice reform. However, the benefits of big data can also be extended to simpler, everyday tasks, such as scheduling. Big Data Offers […]

Automated Hyperparameter Tuning, Scaling and Tracking: On-Demand Webinar and FAQs now available!

Posted Leave a commentPosted in Data Science, Ecosystem, Engineering Blog, Hyperopt, Hyperparameter Tuning, Machine Learning, MLflow, MLlib

Try this notebook in Databricks On June 20th, our team hosted a live webinar—Automated Hyperparameter Tuning, Scaling and Tracking on Databricks—with Joseph Bradley,  Software Engineer, and Yifan Cao, Senior Product Manager at Databricks. Automated Machine Learning (AutoML) has received significant interest recently because of its ability to shorten time-to-value for data science teams and maximize […]

can overemphasis on data scalability compromise data quality?

Posted Leave a commentPosted in Big Data, Data Quality, Data Science, scalability

I first heard the term “big data” five years ago. The concept has really changed our lives in spectacular ways. Unfortunately, the term itself might be leading decision-makers astray. They believe that the value of big data is predicated almost entirely on its volume. The people that have sensationalized the concept of big data deserve […]

Luck, talent and covering our Bayes-es in batting

Posted Leave a commentPosted in Analytics, Cricket, Data Science, India, Rohit Sharma, sports

“India beat Pakistan after ruthless Rohit Sharma sets insurmountable target at Cricket World Cup” — The Telegraph “India vs Pakistan: Rohit Sharma’s 140 sets up victory for Virat Kohli’s side” — BBC Sport ”India vs Pak: Rohit Sharma smashes 140, his 2nd ton of World Cup 2019″— The Economic Times I come into work, it’s […]

What’s new with MLflow? On-Demand Webinar and FAQs now available!

Posted Leave a commentPosted in Data Science, Engineering Blog, Machine Learning, Managed MLflow, MLflow, Model Management, Open Source

On June 6th, our team hosted a live webinar—Managing the Complete Machine Learning Lifecycle: What’s new with MLflow—with Clemens Mewald, Director of Product Management at Databricks. Machine learning development brings many new complexities beyond the traditional software development lifecycle. Unlike in traditional software development, ML developers want to try multiple algorithms, tools and parameters to […]

5 ways data science can help you work smarter, not harder

Posted Leave a commentPosted in data, Data Science, sentiment analysis, trends

Today, the internet bleeds into almost every facet of everyday life — it empowers our productivity, enhances our entertainment, and enables our communication. As it does these things, of course, it generates a vast quantity of data: rich, complex, wide-reaching data on everything from the money we spend to the websites we visit. Data science […]