EZE IFEANYIforThe Journey of ezzescienceezzescience.hashnode.net·Jan 30, 2023Python in English: Simple Optimization 2In my previous article, we discussed about rice, beans, meat and a little bit about the linear programming module of the Scipy optimize library (❁´◡`❁). It was a good introduction to the concept of optimization and was shown with an everyday scenario...Discuss·2 likes·40 readsPython
David ChongforMLOps, Productivity & Life Hacksdavidcjw.hashnode.net·Jun 19, 2022Why We Use Sparse Matrices for Recommender SystemsIn recommender systems, we typically work with very sparse matrices as the item universe is very large while a single user typically interacts with a very small subset of the item universe. Take YouTube for example — a user typically watches hundreds...Discuss·34 readsMachine Learning
Nikhil RaoforNikhil Rao's Blognrao57.hashnode.net·Aug 7, 2022Maximize Profit with Scipy OptimizeThe problem is a classic product mix-problem, where the objective is to maximize profit given some production and ingredients constraints, in this case it is a coffee shop with three coffee types. x0 -> Regular x1 -> Latte x2 -> Mocha Constraints: x0...Discuss·100 readsPython
EZE IFEANYIforThe Journey of ezzescienceezzescience.hashnode.net·Jan 30, 2023Python in English: Simple Optimization 2In my previous article, we discussed about rice, beans, meat and a little bit about the linear programming module of the Scipy optimize library (❁´◡`❁). It was a good introduction to the concept of optimization and was shown with an everyday scenario...Discuss·2 likes·40 readsPython
Nikhil RaoforNikhil Rao's Blognrao57.hashnode.net·Aug 7, 2022Maximize Profit with Scipy OptimizeThe problem is a classic product mix-problem, where the objective is to maximize profit given some production and ingredients constraints, in this case it is a coffee shop with three coffee types. x0 -> Regular x1 -> Latte x2 -> Mocha Constraints: x0...Discuss·100 readsPython
David ChongforMLOps, Productivity & Life Hacksdavidcjw.hashnode.net·Jun 19, 2022Why We Use Sparse Matrices for Recommender SystemsIn recommender systems, we typically work with very sparse matrices as the item universe is very large while a single user typically interacts with a very small subset of the item universe. Take YouTube for example — a user typically watches hundreds...Discuss·34 readsMachine Learning
