Category Archives: Reinforcement Learning

Deep Reinforcement Learning with RLlib and TensorFlow for Price Optimization

Deep Learning has made serious inroads into Reinforcement Learning. Deep Reinforcement Learning(DRL) has been  used successfully for playing Atari games. Beyond games, Reinforcement Learning(RL) is applicable for any decision making problem under uncertain conditions e.g autonomous vehicles, business decision making … Continue reading

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Optimizing Discount Price for Perishable Products with Thompson Sampling using Spark

For retailers, stocking perishable products is a risky business. If a product doesn’t sell completely by the expiry date, then the remaining inventory has to be discarded and loss be taken for those items. Retailers will do whatever is necessary … Continue reading

Posted in AI, Big Data, Data Science, Reinforcement Learning, Scala, Spark | Tagged , | 2 Comments

Tracking Web Site Bounce Rate in Real Time

Bounce rate for a page  in a web site, is the  proportion of sessions with only that page in the session. This post will show how to calculate bounce rate in real time with Storm using web log data. We … Continue reading

Posted in Big Data, Optimization, Real Time Processing, Reinforcement Learning, Storm, Web Analytic | Tagged , | 2 Comments

Boost Lead Generation with Online Reinforcement Learning

When I go to a web site for for downloading white paper or product data sheet,  I often  hit the back button if presented with a form asking for lots of personal data. Any user that bounces out, is a … Continue reading

Posted in Big Data, Data Science, Real Time Processing, Redis, Reinforcement Learning, Storm | Tagged , , , | 2 Comments

Bandits Know the Best Product Price

In an earlier post, I did a survey of a class of reinforcement learning  algorithms, known as Multi Arm Bandit(MAB) . Essentially, these algorithms make decisions and learn from rewards received from the environment. You can also think of them as … Continue reading

Posted in Big Data, Data Science, Hadoop and Map Reduce, Marketing Analytic, Optimizatiom, Optimization, Reinforcement Learning | Tagged , , , | 4 Comments

A Learning but Greedy Gambler

In multi-armed bandit (MAB)  problem, a gambler must decide which arm of K slot machines to pull in sequence of N rounds of pulls to maximize the overall return. Many real life optimization and decision making problems can be modelled … Continue reading

Posted in Big Data, Data Science, Hadoop and Map Reduce, Marketing Analytic, Optimization, Reinforcement Learning, Storm | Tagged | 5 Comments