tensor-house
lolesports-predictor
| tensor-house | lolesports-predictor | |
|---|---|---|
| 4 | 1 | |
| 1,163 | 4 | |
| - | - | |
| 7.5 | 3.2 | |
| 3 months ago | almost 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tensor-house
-
Supply Chain Uses Cases
I still have this on my reading list, it has quite some interesting SC applications. https://github.com/ikatsov/tensor-house
-
How to use the code to do analysis with my data
Hi, how can i use the code of an analysis like this https://github.com/ikatsov/tensor-house/blob/master/pricing/price-optimization-multiple-time-intervals.ipynb but with my data?
-
What are some applications of Data Science in Digital Marketing?
This is the companion github to the book, it doesn't have all the use cases, but there are a decent amount of code samples to get you started.
-
Machine learning Applications in Marketing
Happy to help out! That website I linked has a link to the book PDF, so you can check it out yourself. I guess the Amazon reviews must have missed it, but there is a companion github for a selection of models in the book that may be helpful.
lolesports-predictor
What are some alternatives?
EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
models - A collection of pre-trained, state-of-the-art models in the ONNX format
Artificial-Intelligence-Projects - Collection of Artificial Intelligence projects.
Workshops - Workshops organized to introduce students to security, AI, blockchain, AR/VR, hardware and software
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
models - Models and examples built with TensorFlow
vectordb-recipes - High quality resources & applications for LLMs, multi-modal models and VectorDBs
mta - Multi-Touch Attribution
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.