Machinelearning, ai, datascience, ml & much more…
AI News Sunday, July 1
- Don’t be afraid of artificial intelligence managing your money
- RippleMatch uses AI to help students line up work after college
- insideBIGDATA “Ask a Data Scientist” Series – insideBIGDATA
- A Non-Technical Introduction to Machine Learning – SafeGraph
MachineLearning, ML, AI
- How to overcome the challenges of customer experience disruption
- Industry 4.0 – “Smart Factory” explained
4IR, Industry40, ML, DL, AI
- Robot with artificial intelligence about to invade space
- error – University of Gothenburg, Sweden
AI, deeplearning, robotics
- The Brexit Short: How Hedge Funds Used Private Polls to Make Millions – Bloomberg
- Artificial intelligence robot launched to ISS from US
- While this might sound like a futuristic science fiction novel, its already happening in financial services.
- Robots and smart computers are helping to manage your money, and they will enable banks to increase revenue and employment over the next five years, according to a report by Accenture on realizing the full value of AI.
- Artificial intelligence refers to computer systems that are able to perform tasks that historically required human intelligence, such such as recognizing images, understanding speech, translating languages and making decisions.
- Some examples of artificial intelligence in financial services are mobile checking deposits that read checks, custom notifications that flag high payments and specific transfer reminders.
- While the assistant is only for corporate clients right now, other banks have launched virtual assistants that use AI technology for retail customers.
@jimpavia: Don’t be afraid of artificial intelligence managing your money https://t.co/NT8VWBWBOo @csreinicke
- Thats why Yale graduates Eric Ho and Andrew Myers created RippleMatch, a machine learning-powered recruitment tool for college students.
- Image Credit: RippleMatch – – – Their end-to-end solution connects employers with vetted, highly qualified college seniors who might not have years of job experience under their belts, but who share values, beliefs, and core competencies with candidate profiles hiring managers define.
- Image Credit: RippleMatch – – – Myers and Ho, taking cues from the competition,focused on making the onboarding process as quick and painless as possible.
- Myers and Ho took a grassroots approach to building out RippleMatch, targeting the top clubs and organizations on over 100 college campuses including Yale, Harvard, and Stanford.
- They claim that a quarter of Ivy League seniors are using RippleMatch to find a job, and that 60 percent of candidates are selected for a first-round interview.
@att_everything: RippleMatch uses AI to help students line up work after college https://t.co/g8Eh7SGwDj#MachineLearning #ai… https://t.co/Qz7mvjpphR
- Welcome to the series of articles sponsored by Intel Ask a Data Scientist from insideBIGDATAs popular Data Science 101 channel.
- These articles constitute many of our sites most popular resources for newbie data scientists.
- The 12 articles listed below were from reader submitted questions of varying levels of technical detail and answered by a practicing data scientist sometimes by me and other times by an Intel data scientist.
- We tried to cover common topics that we typically see asked by those transitioning to data science from other fields, or just generally people who are busy retooling for a career in this dynamic field.
- In addition to being a tech journalist, Daniel also is a practicing data scientist, author, educator and sits on a number of advisory boards for various start-up companies.
@IainLJBrown: insideBIGDATA “Ask a Data Scientist” SeriesRead more here: https://t.co/xXjhtof8IU#DataScience #MachineLearning… https://t.co/M4TRZRncZJ
- The field itself: ML is a field of study which harnesses principles of computer science and statistics to create statistical models.
- Models: Teaching a computer to make predictions involves feeding data into machine learning models, which are representations of how the world supposedly works.
- Machine learning of all types uses models and algorithms as its building blocks to make predictions and inferences about the world.
- Most common statistical models are constructed using a technique called supervised learning, which uses data that includes a response variable to make predictions or do inference.
- Naturally, there are many different types of models which explain how the data actually works, and wed like to choose the one that most accurately describes the relationship between the predictors and the response variable.
@Ronald_vanLoon: A Non-Technical Introduction to #MachineLearningby @noahyonack @Medium |https://t.co/CQBbzQ0p8H#ML #AI… https://t.co/50TCLz9STs
@IainLJBrown: How to overcome the challenges of customer experience disruptionRead more here: https://t.co/0Bh1I2mGRS#BigData… https://t.co/NyH0QVgs6S
@JeffreyBuskey: Industry 4.0 – “Smart Factory” explained https://t.co/giQsYdrRB1 via @YouTube #4IR #Industry40 #ML #DL #AI… https://t.co/KgH2wNCBld
@fcain: A new robotic astronaut companion is on its way to the space station – https://t.co/vdkZE4UV8b https://t.co/M6osXiLJtb
@nordicinst: Artificial Intelligence specialization. #AI #deeplearning #robotics https://t.co/fVvrAfV9rT
@fintechreality: Brexit’s Big Short: How Pollsters Helped Hedge Funds Beat the Crash https://t.co/RQzIL3stWv #innovation #AI… https://t.co/CNSLoApNyG
@IainLJBrown: Artificial intelligence robot launched to ISS from USRead more here: https://t.co/6FlGQBqlqz… https://t.co/M2oR63TdKT
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