SpringML,a leader in machine learning and advanced data analytics services,announced that it has achieved the renewed Machine Learning Partner Specialization in the Google Cloud Partner Advantage Program. By earning the Machine Learning Partner Specialization, SpringML has shown its expertise and success in building customer solutions in the Machine Learning field using Google Cloud technology. Partners achieving this specialization have demonstrated success with data exploration, preprocessing, model training, model evaluation, model deployment, online prediction, and Google pretrained Machine Learning APIs. This specialization will further enable customers to leverage Google Cloud AI and machine learning services to analyze data, use speech and image recognition applications, and more. "Artificial intelligence and machine learning is one of the core foundations of a successful digital transformation. By using the Google Cloud ML tools & technologies, SpringML has helped enterprises in their digital transformation journey." said Prabhu Palanisamy, President and Chief Strategy Officer at SpringML.

Organizations are turning to machine learning (ML) and artificial intelligence (AI) as a path to innovation and product and service differentiation, but too many organizations are stalled at the proof-of-concept stage. Register to attend and you'll learn: Join us on Feb 28 11 AM PT/2 PM ET to learn how to take a more industrialized and automated approach to developing and deploying ML and DL models across your enterprise.

Time flies when you are having fun. It's been 4 years since Einstein Analytics was launched! Since then Salesforce has added a long list of features every release and integrated Einstein Platform to Sales, Service, Marketing and Commerce Clouds. AI will continue to be a big focus across Dreamforce 2018 and there will be a lot of discussion on Artificial Intelligence with Salesforce Einstein. We can help you understand the ins and outs of the Einstein implementation for your organization.

SpringML is thrilled to be a Velocity Sponsor and participate in one of the premier technology events of the year, showcasing the newest advancements in Machine Learning and Artificial Intelligence. Take a quick scroll to see what we're showcasing at Google Next below. Take a little time after the first day of the conference to unwind with SpringML! Please RSVP using the link below to indicate your interest in joining us. Contact us to set up a one-on-one conference with members of SpringML to see how we can apply the newest Machine Learning technologies to your business' use cases.

Next Word Prediction or what is also called Language Modeling is the task of predicting what word comes next. It is one of the fundamental tasks of NLP and has many applications. You might be using it daily when you write texts or emails without realizing it. I recently built a next word predictor on Tensorflow and in this blog I want to go through the steps I followed so you can replicate them and build your own word predictor. I used the text8 dataset which is en English Wikipedia dump from Mar 2006.

Struggling to keep up with unrelenting inbound service requests? The first step toward responsive, high-scale customer service is accurately identifying the issues or questions and channeling the inquiries to the right parties. Tapping machine learning and natural language processing, commercial real estate giant CBRE put in place an automated call-routing solution capable of handling millions of service requests per year. Join us on March 6th at 10 AM Pacific for this webinar and learn more about cutting-edge customer service from expert panelists Doug Henschen, VP and Principal Analyst at Constellation Research, Girish Reddy, CTO at SpringML, Google Cloud Platform Premier Partner with Machine Learning Specialization, and Stuart Appley, Managing Director, Global Workplace Solutions, at CBRE. How to get started in this AI journey for automated case routing for your organization?

Just in time for the holiday lull, here is a fun ML project that processes a popular movie-clip down to the actor's face and biography in a fully automated pipeline and in near real time! It's all done in around 200 lines of code. This may seem like a lot of code, but just five years ago it would have required tens of thousands of lines and a headache. At SpringML, we've built many solutions using the versatile Google Cloud suite of APIs but some of the funnest projects have been working with the Google Video Intelligence and Vision APIs in particular. Leveraging these two powerful APIs is like having an army of convolutional neural-network PhDs at your beck and call.

Today's guest blog is written by SpringML. SpringML provides predictive analytics and sales forecasting applications that apply machine learning to today's most pressing sales problems. Sales leaders get the insights they need to close more deals and drive business growth. You're a sales leader who manages a team of busy sales professionals who often do not have time to learn new technology or change up current processes. Being the proactive manager that you are, you put together a presentation that explains how machine learning will help your sales professionals make more money and be much more efficient.