Home Big Data Cloudera and AMD Spur Knowledge Scientists to Take Local weather Motion

Cloudera and AMD Spur Knowledge Scientists to Take Local weather Motion

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Cloudera and AMD Spur Knowledge Scientists to Take Local weather Motion

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The world faces a number of environmental sustainability challenges — from the local weather disaster and water shortage to meals manufacturing and concrete resilience. Overcoming these hurdles affords alternatives for innovation by means of know-how and synthetic intelligence.

That’s why Cloudera and AMD have partnered to host the Local weather and Sustainability Hackathon. The occasion invitations people or groups of knowledge scientists to develop an end-to-end machine studying mission targeted on fixing one of many many environmental sustainability challenges going through the world at present. 

Individuals will probably be given entry to Cloudera Machine Studying operating on AMD {hardware} to allow swift, highly effective computations and breakthrough improvements — a pairing that may assist information scientists craft local weather and sustainability options. On the completion of this hackathon, each line of code from the successful prototypes will probably be made public in order that the occasion can contribute to the collective effort to handle the local weather disaster and different urgent environmental sustainability challenges.

This isn’t your extraordinary hackathon — it’s meant to yield actual, actionable local weather options powered by machine studying. Individuals can select from the next classes for his or her prototype:

  • Local weather Sensible Agriculture: With the world’s inhabitants anticipated to hit practically 10 billion by 2050, discovering sustainable methods to feed all of those folks is essential for addressing world starvation in addition to mitigating the local weather disaster. Local weather-smart agriculture (CSA) is an built-in strategy to managing landscapes — cropland, livestock, forests and fisheries — that tackle the interlinked challenges of meals safety and local weather change. Machine studying (ML) has the potential to advance climate-smart agriculture by offering beneficial insights, predictions, and resolution help to farmers, researchers, and policymakers. This contains local weather modeling and prediction, crop yield prediction, pest and illness detection, irrigation administration, precision agriculture, soil well being evaluation, crop choice and rotation, carbon sequestration, provide chain optimization, resolution help techniques, local weather adaptation methods, and data-driven analysis.
  • The Water Disaster: Whereas water is one thing many take without any consideration, its shortage is changing into some of the urgent sustainability challenges for companies, governments, communities, and people all over the world. Moreover being elementary to sustaining life, water is also integral for agriculture, manufacturing, and industrial processes. The local weather disaster is a water disaster, too. Because the planet warms, this results in elevated evaporation, altering and unpredictable precipitation patterns, rising sea ranges, and melting snow pack and glaciers, amongst different challenges. Addressing water shortage is changing into a essential difficulty. Attainable initiatives embrace forecasting water consumption primarily based on historic information, climate information, and inhabitants progress; utilizing satellite tv for pc imagery to detect adjustments within the setting which may point out underground leaks in giant pipelines; or predicting the quantity of rainwater that may be harvested in particular areas primarily based on climate forecasts and historic information to assist in designing efficient rainwater harvesting techniques. 
  • Sustainable Cities: Cities are answerable for 70 % of worldwide greenhouse gasoline emissions. That signifies that the local weather disaster will probably be received or misplaced in our city environments. Many of those emissions are pushed by industrial and transportation techniques reliant on fossil fuels. However machine studying and large information supply promise for growing the good cities of tomorrow. By enhancing efficiencies and enabling higher decision-making, we are able to tackle the sustainability challenges afflicting cities all over the world. Attainable initiatives embrace air high quality prediction and monitoring, Predicting power demand in several elements of the town to optimize electrical energy distribution, or utilizing imagery to categorise waste varieties for extra environment friendly recycling processes.

For this Hackathon, individuals will probably be tasked with utilizing publicly out there datasets (strategies for every theme are supplied) to create their very own distinctive Utilized ML Prototype (AMP) targeted on fixing or gaining additional perception right into a local weather or sustainability problem. Cloduera’s Utilized Machine Studying Prototypes are totally constructed end-to-end information science initiatives that may be deployed with a single click on straight from Cloudera Machine Studying, or accessed and constructed your self through public GitHub repositories..

The local weather disaster received’t wait — we hope you’ll be part of us in utilizing the facility of knowledge science and machine studying to assist tackle it as soon as and for all. Study extra about how one can take part within the hackathon right here.

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