This recipe requires 1lb of grated Parmigiano Reggiano cheese, 1lb of fresh cut pasta, and 1lb of tomato basil sauce to prepare a classic pasta dish. The key ingredients are fresh pasta, tomato sauce flavored with basil, and grated Parmesan cheese.
GetLinkedInHelp.com Presentation on How to Socially Sell Your Way to More Clo...GetLinkedInHelp.com
This is the exact presentation that Kristina Jaramillo (Managing Partner at GetLinkedInHelp.com) is using with her speech at the 2016 Manufacturing Sales Summit. View this presentation to see how to go from connection to sales opportunity and revenue on LinkedIn.
In the past, selling has involved building a rock-solid relationship with one key decision maker. However, in today's social selling environment, developing a relationship with a single person is no longer sufficient.
According to Demand Gen Report’s 2014 Buyer Behavior Survey, 34% of buyers noted a yearly increase in the number of people involved in purchasing decisions.
For this reason, relying too much on one relationship is risky.
Join us for this webinar as we dive into how to sell to multiple decision makers.
Presented by: Mac Witmer, Relationship Manager, LinkedIn Sales Solutions
Analyzing Air Quality Measurements in Macedonia with Apache DrillMarjan Sterjev
The article provides an example for JSON data analysis with Apache Drill. The "toy" model is based on the publicly available air quality measurement data.
Braxton McKee, CEO & Founder, Ufora at MLconf NYC - 4/15/16MLconf
Say What You Mean: Scaling Machine Learning Algorithms Directly from Source Code: Scaling machine learning applications is hard. Even with powerful systems like Spark, Tensor Flow, and Theano, the code you write has more to do with getting these systems to work at all than it does with your algorithm itself. But it doesn’t have to be this way!
In this talk, I’ll discuss an alternate approach we’ve taken with Pyfora, an open-source platform for scalable machine learning and data science in Python. I’ll show how it produces efficient, large scale machine learning implementations directly from the source code of single-threaded Python programs. Instead of programming to a complex API, you can simply say what you mean and move on. I’ll show some classes of problem where this approach truly shines, discuss some practical realities of developing the system, and I’ll talk about some future directions for the project.
Erich Elsen, Research Scientist, Baidu Research at MLconf NYC - 4/15/16MLconf
Training Recurrent Neural Networks at Scale: One of our projects at Baidu’s Silicon Valley AI Lab is using deep learning to develop state of the art end-to-end speech recognition systems based on recurrent neural networks for multiple languages. The training set for each language is multiple terabytes in size and each model requires in excess of 10 Exaflops to train. Training such models requires scale and techniques that are unusual for deep learning but more common in high performance computing. I will talk about the challenges involved and the software and hardware solutions that we employ.
GetLinkedInHelp.com Presentation on How to Socially Sell Your Way to More Clo...GetLinkedInHelp.com
This is the exact presentation that Kristina Jaramillo (Managing Partner at GetLinkedInHelp.com) is using with her speech at the 2016 Manufacturing Sales Summit. View this presentation to see how to go from connection to sales opportunity and revenue on LinkedIn.
In the past, selling has involved building a rock-solid relationship with one key decision maker. However, in today's social selling environment, developing a relationship with a single person is no longer sufficient.
According to Demand Gen Report’s 2014 Buyer Behavior Survey, 34% of buyers noted a yearly increase in the number of people involved in purchasing decisions.
For this reason, relying too much on one relationship is risky.
Join us for this webinar as we dive into how to sell to multiple decision makers.
Presented by: Mac Witmer, Relationship Manager, LinkedIn Sales Solutions
Analyzing Air Quality Measurements in Macedonia with Apache DrillMarjan Sterjev
The article provides an example for JSON data analysis with Apache Drill. The "toy" model is based on the publicly available air quality measurement data.
Braxton McKee, CEO & Founder, Ufora at MLconf NYC - 4/15/16MLconf
Say What You Mean: Scaling Machine Learning Algorithms Directly from Source Code: Scaling machine learning applications is hard. Even with powerful systems like Spark, Tensor Flow, and Theano, the code you write has more to do with getting these systems to work at all than it does with your algorithm itself. But it doesn’t have to be this way!
In this talk, I’ll discuss an alternate approach we’ve taken with Pyfora, an open-source platform for scalable machine learning and data science in Python. I’ll show how it produces efficient, large scale machine learning implementations directly from the source code of single-threaded Python programs. Instead of programming to a complex API, you can simply say what you mean and move on. I’ll show some classes of problem where this approach truly shines, discuss some practical realities of developing the system, and I’ll talk about some future directions for the project.
Erich Elsen, Research Scientist, Baidu Research at MLconf NYC - 4/15/16MLconf
Training Recurrent Neural Networks at Scale: One of our projects at Baidu’s Silicon Valley AI Lab is using deep learning to develop state of the art end-to-end speech recognition systems based on recurrent neural networks for multiple languages. The training set for each language is multiple terabytes in size and each model requires in excess of 10 Exaflops to train. Training such models requires scale and techniques that are unusual for deep learning but more common in high performance computing. I will talk about the challenges involved and the software and hardware solutions that we employ.
