Tracksuit
Latana
YouGov
FeedbackSpark
Back Market
Zazzy
Love & Robots
Group Caliber
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
htm.java
Tracksuit has created beautiful, always-on, and radically affordable brand tracking for modern consumer brands. Brand marketers and leaders at consumer brands have access to enterprise-tier brand tracking, specifically built for them, at a price point that works. Teams can easily track awareness, consideration, preference and brand associations from real humans within the wider market, and compare results against competitors.
Tracksuit Scikit-learnBased on our record, Scikit-learn seems to be more popular. It has been mentiond 29 times since March 2021. 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.
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 15 days ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 4 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / about 1 year ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Latana - Latana is the first brand tracking tool to use advanced data science to ensure reliable and accurate brand insights.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
YouGov - YouGov is a global public opinion and data company. Explore what the world thinks, discover our solutions, and join our community to share your opinion.
OpenCV - OpenCV is the world's biggest computer vision library
FeedbackSpark - FeedbackSpark is in-product micro survey tool that helps product teams to remove guesswork from product development. Harness the voice of customer to drive product success.
NumPy - NumPy is the fundamental package for scientific computing with Python