Analytics Vidhya
MARCH 27, 2019
Introduction Q-learning became a household name in data science when DeepMind came up with an algorithm that reached superhuman levels on ATARI games. It’s. The post Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning appeared first on Analytics Vidhya.
O'Reilly on Data
MARCH 27, 2019
Watch highlights from expert talks covering AI, machine learning, data analytics, and more. People from across the data world are coming together in San Francisco for the Strata Data Conference. Below you'll find links to highlights from the event. The journey to the data-driven enterprise from the edge to AI. Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data.
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Corinium
MARCH 27, 2019
Investment managers are expected to spend more than $1.6 billion on alternative data sets in 2020. The sheer volume of data produced will necessitate a change in how businesses acquire, process, and use it. Identifying and acquiring data sets is only the beginning of an investment firm’s data strategy. The key will be the ability to integrate a broad range of custom data sets, to share them flexibly, and to extract key insights in time.
datapine
MARCH 27, 2019
“Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.” – Steve Jobs. We’re living in the midst of the age of information, a time when online data analysis can determine the direction and cement the success of a business or a startup that decides to dig deeper into consumer behavior insights.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
O'Reilly on Data
MARCH 27, 2019
Shafi Goldwasser explains why the next frontier of cryptography will help establish safe machine learning. Continue reading AI and cryptography: Challenges and opportunities.
Smart Data Collective
MARCH 27, 2019
“Google Search Reveals Community College Student’s Social Security Number.” While this may seem like a headline you would find on sites like The Onion , this is something that actually happened. This situation occurred when staff members at a community college started to test a new type of online application that utilized files full of sensitive and unaltered data on a server that was not secure.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Insight
MARCH 27, 2019
DeepAugment is an AutoML tool focusing on data augmentation. It utilizes Bayesian optimization for discovering data augmentation strategies tailored to your image dataset. The main benefits and features of DeepAugment are: Reduces the error rate of CNN models (showed 60% decrease in error for CIFAR10 on WRN-28–10) Saves time by automating the process 50 times faster than Google’s previous solution– AutoAugment The finished package is on PyPI.
O'Reilly on Data
MARCH 27, 2019
Dinesh Nirmal shares a data asset framework that incorporates current business structures and the elements you need for an AI-fluent data platform. Continue reading Streamlining your data assets: A strategy for the journey to AI.
Sisense
MARCH 27, 2019
It’s becoming increasingly obvious that the pace at which we create new data won’t slow down anytime soon. With millions of streams and touch points, most businesses create gigabytes of data every minute, yet our rate of data comprehension cannot keep up. To get the most out of data, companies need to analyze it as soon as it is created—when it can provide the most immediate and relevant insights.
O'Reilly on Data
MARCH 27, 2019
Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data. Continue reading The journey to the data-driven enterprise from the edge to AI.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.
IBM Big Data Hub
MARCH 27, 2019
IBM anticipated barriers to scaling enterprise AI. We developed a platform to help clients operationalize AI faster while infusing trust and transparency with IBM Cloud Private for Data and the add-on Watson OpenScale.
O'Reilly on Data
MARCH 27, 2019
Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise.
Cloudera
MARCH 27, 2019
Cloudera’s vision of delivering Edge to AI solutions using the Enterprise Data Cloud will enable enterprises to transform dramatically. In today’s digitally connected enterprises, data originates from the edge, streams into the data center, lands in an Enterprise Data Cloud for downstream processing including Machine Learning and then serves back to the edge for real-time prediction and action.
Smart Data Collective
MARCH 27, 2019
. Frugal living has become a major fad since the onset of the recession in 2008. In particular, extreme couponing has become a hobby that is practiced by tens of thousands of people all over the United States. Consumers saved $3.1 billion with coupons in 2017. However, in the quest to save money through couponing, many people don’t get the value they are looking for.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
Data Virtualization
MARCH 27, 2019
With data becoming the brain food to the intelligence of every organization, regardless of size or sector, it has become crucial to harness this data to achieve the best results, make the most informed decisions and improve productivity. However, with.
Jedox
MARCH 27, 2019
Best-in-class CRM tools are a must for any company that wants to maintain its competitive edge. Yet despite all of their fancy features and functions, most leading systems fall short when it comes to planning. So what’s a sales professional to do – resort to spreadsheets despite all of the known risks and shortcomings? Fortunately, today there are better options: like lean, cloud-based sales planning software that takes even the best CRM to a whole new level.
Domino Data Lab
MARCH 27, 2019
Special thanks to Addison-Wesley Professional for permission to excerpt the following “Manipulating data with dplyr” chapter from the book, Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R. Domino has created a complementary project. . Introduction. Data scientists spend countless hours wrangling data.
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