Table of contents
TFlearn
TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
As TFlearn is an open source project, you can find more
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on LibHunt.
User-Friendly Interface
TFlearn provides a higher-level API that simplifies the process of building and training deep learning models, making it easier for beginners to use TensorFlow.
Modular Design
It offers modular abstraction layers, allowing users to construct neural networks using pre-defined blocks which are easy to stack and customize.
Integration with TensorFlow
TFlearn is built on top of TensorFlow, providing the flexibility and performance benefits of TensorFlow while enhancing its usability.
Pre-built Models
It includes a range of pre-built models and algorithms for common machine learning tasks like classification and regression, facilitating quick experimentation.
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Check the traffic stats of TFlearn on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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The latest comments about TFlearn on Reddit. This can help you find out how popualr the product is and what people think about it.
TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / almost 3 years ago
Both the teams in a game are given their individual ID values and are made into vectors. Relevant data like the home and away team, home runs, RBI’s, and walk’s are all taken into account and passed through layers. There’s no need to reinvent the wheel here, there's a multitude of libraries that enable a coder to implement machine learning theories efficiently. In this case we will be using a library called... - Source: dev.to / about 4 years ago
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