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Google Cloud Machine Learning VS TFlearn

Compare Google Cloud Machine Learning VS TFlearn and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Google Cloud Machine Learning logo Google Cloud Machine Learning

Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Google Cloud Machine Learning Landing page
    Landing page //
    2023-09-12
Not present

Google Cloud Machine Learning videos

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TFlearn videos

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Face Recognition using Deep Learning | Convolutional-Neural-Network | TensorFlow | TfLearn

Category Popularity

0-100% (relative to Google Cloud Machine Learning and TFlearn)

Google Cloud Machine Learning

TFlearn

Data Science And Machine Learning
83 83%
Data Science And Machine Learning
17% 17
OCR
0 0%
OCR
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Python Tools
100 100%
Python Tools
0% 0

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Machine Learning seems to be a lot more popular than TFlearn. While we know about 21 links to Google Cloud Machine Learning, we've tracked only 2 mentions of TFlearn. 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.

Google Cloud Machine Learning mentions (21)

  • Gemini 1.5 outshines GPT-4-Turbo-128K on long code prompts, HVM author
    2. Google Cloud Vertex AI: https://cloud.google.com/vertex-ai. Policy: https://cloud.google.com/vertex-ai/docs/generative-ai/data-governance#foundation_model_training. - Source: Hacker News / 3 months ago
  • Let's build your first ML app in Google Cloud Run
    Google Cloud Platform (GCP) provides a very befitting Machine Learning solution called Vertex Ai that handles Google Cloud's unified platform for building, deploying, and managing machine learning (ML) models. Our goal is to build a simple Machine Learning application that optimizes all that GCP provides plus an implementation of continuous integration and continuous development (CI/CD). - Source: dev.to / 4 months ago
  • Google Gemini Pro API Available Through AI Studio
    Cross posting some links from another post that HNers found helpful - https://cloud.google.com/vertex-ai (marketing page) - https://cloud.google.com/vertex-ai/docs (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console) - https://console.cloud.google.com/vertex-ai/model-garden (all the models) - https://console.cloud.google.com/vertex-ai/generative (studio / playground) VertexAI is the... - Source: Hacker News / 5 months ago
  • Google Imagen 2
    For the peer comments - https://cloud.google.com/vertex-ai (main page) - https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console). - Source: Hacker News / 5 months ago
  • Introducing Gemini: our largest and most capable AI model
    Starting on December 13, developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI. Source: 5 months ago
View more

TFlearn mentions (2)

  • Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)
    TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / over 1 year ago
  • Base ball
    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 3 years ago

What are some alternatives?

When comparing Google Cloud Machine Learning and TFlearn, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Clarifai - The World's AI

NumPy - NumPy is the fundamental package for scientific computing with Python

DeepPy - DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.

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