kaggle-solutions VS dkm

Compare kaggle-solutions vs dkm and see what are their differences.

Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
kaggle-solutions dkm
8 2
3,753 95
- -
6.4 1.5
24 days ago 12 months ago
HTML HTML
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

kaggle-solutions

Posts with mentions or reviews of kaggle-solutions. We have used some of these posts to build our list of alternatives and similar projects.

dkm

Posts with mentions or reviews of dkm. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing kaggle-solutions and dkm you can also consider the following projects:

datascience - Curated list of Python resources for data science.

deep-learning-drizzle - Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

data-science-interviews - Data science interview questions and answers

jube - Jube is an open-source software designed for monitoring transactions and events. It offers a range of powerful features including real-time data wrangling, artificial intelligence, decision making, and case management. Jube's exceptional performance is particularly evident in its application to fraud prevention and abuse detection scenarios.

catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.