datarobot
RapidMiner
Statista
H2O.ai
Montecarlito
IBM ILOG CPLEX Optimization Studio
Displayr
Tibco Data Science
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
datarobotBased on our record, NumPy seems to be a lot more popular than datarobot. While we know about 107 links to NumPy, we've tracked only 1 mention of datarobot. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
To predict what we would have expected, we used the models and approach we developed to predict the knockout stage of the Champions League using data provided by Data Sports Group. We used DataRobot’s models to predict which team would win each match to simulate the final nine matchdays 10,000 times. For each team, we calculated the average number of wins, draws and losses over those 10,000 seasons to build an... Source: about 1 year ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Statista - The Statistics Portal for Market Data, Market Research and Market Studies
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.
OpenCV - OpenCV is the world's biggest computer vision library
