Pinned Repositories
AI_Supply_Chain
This is the code for "AI for Supply Chain" by Siraj Raval on Youtube
amazon-forecast-samples
Notebooks and examples on how to onboard and use various features of Amazon Forecast.
awesome-project-ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
CaiNiao-DemandForecast-StoragePlaning
1st Place Season one & 6th Place Season two
Clustering-Analysis-on-customers-of-a-wholesale-distributor
Project in which unsupervised learning techniques are applied on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data.
coffee-quality-database
Building the Coffee Quality Institute Database
cvrptw
Capacitated Vehicle Routing Problem with Time Windows (NP-Hard). Winner at ICHack 18.
deeptravel
:car: Solving Traveling Salesman Problem (TSP) using Deep Learning
Dynamic-Pricing
This machine learning model (deep and wide learning model) helps us to implement dynamic pricing feature of a supply chain business problem. This model uses tensorflow to solve the problem and can be structured accordingly to run efficiently on Google Cloud Platform.
SCA
pysca's Repositories
pysca/SCA
pysca/amazon-forecast-samples
Notebooks and examples on how to onboard and use various features of Amazon Forecast.
pysca/awesome-project-ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
pysca/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
pysca/imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
pysca/industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries.
pysca/Inventory-Optimization-Algorithms
Algorithms Library for Supply Chain Inventory Optimization
pysca/Inventory-Routing-Problem-IRP-
It can be described as the combination of vehiclerouting and inventory management problems, in which a supplier has to deliver products to a number of geographically dispersed customers, subject to side constraints. It provides integrated logistics solutions by simultaneously optimizing inventory management, vehicle routing, and delivery scheduling. Some exact algorithms and several powerful metaheuristic and matheuristic approaches have been developed for this class of problems, especially in recent years. The purpose of this article is to provide a comprehensive review of this literature, based on a new classification of the problem. We categorize IRPs with respect to their structural variants and the availability of information on customer demand.
pysca/iot-predictive-analytics
Method for Predicting failures in Equipment using Sensor data. Sensors mounted on devices like IoT devices, Automated manufacturing like Robot arms, Process monitoring and Control equipment etc., collect and transmit data on a continuous basis which is Time stamped.
pysca/Kaggle-Bosch
Kaggle Project: Bosch Manufacturing
pysca/KDD-Cup-2019-CAMMTR
Context-Aware Multi-Modal Transportation Recommendation
pysca/Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
pysca/Marketing-and-Retail-Analytics
In the recent past, e-commerce companies have emerged and flourished in the industry. They offer the convenience to order from a wide variety of options from the comfort of one’s home. But how do they offer these “wide variety of options or products”? To be able to meet the demands of the customers, any e-commerce company would obviously need to st
pysca/multi-echelon-inventory-optimization
multi-echelon inventory optimization with SimPy, SciPy, sklearn, and RBFOpt
pysca/Online-Retail-Transactions-of-UK
Analyzing the Online Transactions in UK and the countries who are purchase stuff from them and analyzing the reviews from them using NLP and Machine Learning
pysca/Operations-Research
Some lecture notes of Operations Research (usually taught in Junior year of BS) can be found in this repository along with some Python programming codes to solve numerous problems of Optimization including Travelling Salesman, Minimum Spanning Tree and so on.
pysca/Paddle_baseline_KDD2019
PaddlePaddle baseline for KDD2019 "Context-Aware Multi-Modal Transportation Recommendation"
pysca/practical-machine-learning-with-python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
pysca/Predicting-backorders-in-an-E-com-store-via-ML
Predicting backorders in an E-commerce store to optimize inventory management using Python and Machine Learning.
pysca/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
pysca/SECOM-Detecting-Defected-Items
Anamoly Detection for Detecting Defected Manufactured Semi-Conductors, as in this case of Classification, the Defected Chips would be very less in comparison to perfect Chips so we have apply either Over-Sampling or Under-Sampling.
pysca/seq2seq-signal-prediction
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
pysca/Smart-Inventory-Control-Of-Distribution-Network
GOC(Global Optimization Challange) https://jdata.jd.com/html/detail.html?id=6
pysca/stock-logistics-warehouse
Mirror of OCA/stock-logistics-warehouse that does not include the PRs (optimized for Runbot)
pysca/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
pysca/StockPricePrediction
Stock Price Prediction using Machine Learning Techniques
pysca/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
pysca/TimeSeries_Seq2Seq
This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.
pysca/VRP-RL
Reinforcement Learning for Solving the Vehicle Routing Problem
pysca/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow