I was recently asked to conduct a 2-hour workshop for the State of California Senior Legislators on the topic of “Big Data, Artificial Intelligence and Privacy.” Honored by the privilege of offering my perspective on these critical topics, I shared with my home-state legislators how significant opportunities await the state. I reviewed the once-in-a-generation opportunities awaiting the great State of California (“the State”), where decision makers could vastly…
Added by Bill Schmarzo on February 13, 2018 at 5:30am —
Organizations looking for justification to move beyond legacy reporting should review this little ditty from the healthcare industry:
The Institute of Medicine (IOM) estimates that the United States loses $750 billion annually to medical fraud, inefficiencies, and other siphons in the healthcare system…
Added by Bill Schmarzo on January 26, 2018 at 1:30pm —
Recently 2017 came to a glittering end and as we look back through the lens of technology, the winner was probably Artificial Intelligence aka AI. It received tremendous success as much as some of the industry leaders commented that 2017 was the ‘Year of AI’. This write-up is an attempt to collate the achievements under the academic and industry.
Starting off with academics, the sheer volume of papers published is increasing every year. To give you some statistics,… Continue
Added by Kinnar Kumar Sen on January 25, 2018 at 6:30am —
“Big Data is dead.” “Big Data is passé.”
“We no longer need Big Data; we need Machine Learning now.”
As we end 2017 and look forward to big (data) things in 2018, the most important lessons of 2017 – in fact, maybe the most important lesson going forward – is that Big Data is NOT a thing. Big Data isn’t about the volume, variety or velocity of data any more than car…
Added by Bill Schmarzo on January 20, 2018 at 5:30am —
I was recently a guest lecturer at the University of California Berkeley Extension in San Francisco. On a lovely Saturday afternoon, the classroom was crowded with students of all ages learning the tools of the modern economy. The craftspeople of the “Analytics Revolution” were busy learning new skills and tools that will prepare them for this Brave New World of analytics. I was blown away by their dedication!
As we teach the next generation, it’s important…
Added by Bill Schmarzo on January 19, 2018 at 5:00am —
In this series, I will talk about training a simple neural network on image data. To give a brief overview, neural networks is a kind of supervised learning. By this I mean, the model needs to train on historical data to understand the relationship between input variables and target variables. Once trained, the model can be used to predict target variable on new input data. In the previous posts, we have written about linear, lasso and ridge regression. All those methods come under… Continue
Added by Jobil Louis on January 16, 2018 at 8:00pm —
Most organizations’ IOT Strategy look like a game of ‘Twister’ with progress across important IOT capabilities such as architecture, technology, data, analytics and governance; variables comprising a series of random investments and decisions.…
Added by Bill Schmarzo on January 13, 2018 at 5:00am —
Libratus, the artificial intelligence (AI) engine designed by Professor Tuomas Sandholm at Carnegie Mellon University (CMU) and his graduate student Noam Brown has made an impression on Jason Les, one of the world’s top poker players. Poker News, the poker industry’s online news magazine, recently interviewed Les. A couple questions were telling when asked about which is a better name for his firstborn child and which is the more annoying opponent, Claudico or Libratus. For both questions,… Continue
Added by Ken Strandberg on January 9, 2018 at 3:00pm —
This paper enlightens the way companies can design Intelligent System to understand their customers’ sentiments better to improve their experience, which will help the businesses change their market position.
Sentiment analysis is widely acknowledged in the web and social media monitoring. It allows businesses to gain a comprehensive public opinion on the organization and its services. The ability to deduce insights from the text and emoticons from social media is a… Continue
Added by Valiance Solutions on December 20, 2017 at 1:30am —
What’s the first thing that comes to mind when you hear the following phrases?
- Artificial grass
- Artificial sweeteners
- Artificial flavors
- Artificial plants
- Artificial flowers
- Artificial diamonds and jewelry
- Artificial (fake) news
These phrases probably evoke thoughts such as “fake,” “not real,” or even “shabby.” Artificial is such a harsh adjective.…
Added by Bill Schmarzo on October 30, 2017 at 6:30pm —
Summary: Performance comparison for the popular Deep Learning frameworks supported by Keras – TensorFlow, CNTK, MXNet and Theano
If there are any doubts in regards to the popularity of Keras among the Data Scientist/Engineer community and the mindshare it commands, you just need to look at the support it has been receiving from all major AI and Cloud players. Currently the official Keras release already supports Google's TensorFlow and Microsoft's CNTK deep… Continue
Added by Jasmeet Bhatia on September 14, 2017 at 1:30pm —
Abstract – Big data helps to make strategy for future and understand user behaviors. In 1959, Arther Samuel gave very simple definition of Machine Learning as “a Field of study that gives computer the ability to learn without being explicitly programmed”. Now almost after 58 years from then we still have not progressed much beyond this definition if we compare the progress we made in other areas from same time. The idea of FinTech adopting some best practices from the Big… Continue
Added by Vinod Sharma on August 29, 2017 at 11:00pm —
Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems usually requires manual engineering of features which can then be fed into a machine learning algorithm. Engineering of features generally requires some domain knowledge of the discipline where the data has originated from. For example, if one is dealing with signals (i.e. classification of EEG signals), then possible features would involve… Continue
Added by Burak Himmetoglu on August 22, 2017 at 7:00am —
Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field,…
Added by Sanjiban Sekhar Roy on August 11, 2017 at 8:00am —
The following problems appeared in the first few assignments in the Udacity course Deep Learning (by Google). The descriptions of the problems are taken from the assignments.…
Added by Sandipan Dey on June 17, 2017 at 1:30pm —
When I first started out learning about machine learning algorithms, it turned out to be quite a task to gain an intuition of what the algorithms are doing. Not just because it was difficult to understand all the mathematical theory and notations, but it was also plain boring. When I turned to online tutorials for answers, I could again only see equations or high level explanations without going through the detail in a majority of the cases.… Continue
Added by Jahnavi Mahanta on April 17, 2017 at 9:30am —
When I tell people that I work at an AI company, they often follow up with “So what kind of machine learning/deep learning do you do?” This isn’t surprising, as most of the market attention (and hype) in and around AI has been centered around Machine Learning, and its high profile subset, Deep Learning, and around Natural Language Processing, with the rise of the chatbot and virtual assistants. But while machine learning is a core component for artificial intelligence, AI is in fact more… Continue
Added by Precy Kwan on March 30, 2017 at 8:00am —
There was a recent publication of a story lamenting the shortage of Indian talent in Artificial Intelligence (AI) and related fields. While the article largely focused on the challenges tech startups face while recruiting AI talent, it’s clear from the conversations we have been having with established enterprises that the supply-demand imbalance for AI talent is as acute across company sizes and industries.
What’s the big problem?
As the article… Continue
Added by Rishabh Kaul on March 24, 2017 at 3:00am —
In many cases, you may think that you have a Big Data problem, when in reality you just have a lot of data that a simple sampling can result in great accuracy. In todays blog, I decided to use office room occupancy dataset provided by"Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M.…
Added by Dalila on January 12, 2017 at 9:00am —
This video session features the keynote speaker Professor Geoff Hinton FRS, “Deep Learning”. This lecture was filmed on May 22, 2015.
Watch full video at … Continue
Added by Diego Marinho de Oliveira on April 4, 2016 at 5:32am —