With every platform vendor attempting to democratize machine learning, AutoML is evolving as the future of artificial intelligence. It puts the power of AI in the hands of business analysts and technology decision makers.
Why AutoML Is Set To Become The Future Of Artificial Intelligence
When businesses identify a problem that can be solved through machine learning, they brief the data scientists and analysts to create a predictive analytics solution. In many cases, the turnaround time for delivering a solution is pretty long.
Even for experienced data scientists, evolving machine learning models that can accurately predict the results is always challenging and time-consuming. The complex workflow involved in machine learning models have multiple stages. Some of the significant steps include data acquisition, data exploration, feature engineering, model selection, experimentation and prediction.
There are multiple teams that get involved in arriving at the solution. Data engineering team works on data acquisition and preparation. Data scientists focus on experimentation and optimization of models. DevOps teams own the development environment, tooling, and hosting the inference models in production.
One trend that’s going to fundamentally change the face of ML-based solutions is AutoML. It is going to enable business analysts and developers to evolve machine learning models that can address complex scenarios.
AutoML focuses on two aspects ‘ Data acquisition and prediction. All the steps that take place in between these two phases will be abstracted by the AutoML platform. Essentially, users bring their own dataset, identify the labels, and push a button to generate a thoroughly trained and optimized model that’s ready to predict.
- Publisher: Forbes
- Date: 2018-04-15
- Author: Janakiram MSV
- Twitter: @forbes
- Citation: Web link
Not to change the topic here:
Artificial intelligence coming to life in financial advice
Imaginearriving to work in the morning — the lights already powered on, the temperature set the way you like it, the coffee brewed — and being greeted by an assistant that spent all night preparing a prioritized list of opportunities for you and your clients. “Your client, Jessica, had questions last night about recent volatility affecting her portfolio,” Alexa tells you. “I provided an update on her balance and shared your analysis of the stock market, but she has additional questions for you. You have a call scheduled for 10:30. “I also detected an opportunity for…
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- Date: 2018-04-14
- Author: ‘
‘Ryan W. Neal’
- Citation: Web link
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Key Topics Covered: 1 Table of Contents2 Introduction3 Key Takeaways4 Artificial Intelligence in Retail Market Landscape5 Global Artificial Intelligence in Retail Market – Key Industry Dynamics6 Artificial Intelligence in Retail Market – Global7 Global Artificial Intelligence in Retail Market Analysis – by Retail Format8 Global Artificial Intelligence in Retail Market Analysis – by Technology9 Global Artificial Intelligence in Retail Market Analysis – by Application10 Global Artificial Intelligence in Retail Market – Geographical Analysis11 Industry Landscape12 Competitive Landscape13 Key Company Profiles
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- Author: Research and Markets
- Twitter: @PRNewswire
- Citation: Web link