Keras Reviews

Magic Playlist Reviews

Keras mentions (31)

• My Favorite DevTools to Build AI/ML Applications!

  As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 1 month ago

• Getting Started with Gemma Models

  After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 2 months ago

• How popular are libraries in each technology

  Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago

• Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!

  I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago

• How to query pandas DataFrames with SQL

  Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more. - Source: dev.to / over 1 year ago

Magic Playlist mentions (6)

• For real, does anyone else have this problem? I listen to the sand ~five records every night. I want to diversify, but I love the comfort of the familiar

  Try this site out. It’s basically a similar to this music finder. I do encourage you to try and expand your tastes, but it’s definitely a habit to listen to use music, so ease into it! I usually make a goal of 3 new albums a week. Magic playlist. Source: over 2 years ago

• Tips for efficient digging sessions

  In regards to OP’s question, lately I’ve been digging through genre specific sub-Reddits. There are tonnes of people out there who are absolutely obsessive about their love of certain artists. If I’m digging someone’s taste, I might go look at their comment history to see what else they like. I might then take any of the tunes that I find, plug them into Magic Playlist and then flip through the suggested tracks... Source: over 2 years ago

• Music discovery

  MagicList will do that for you. I can't recall if it'll make a direct connect with Apple Music or if you have to import it from Spotify using SongShift. Source: almost 3 years ago

• I almost never like the music in my Discover Weekly playlist... Anyone else?

  My kids have completely fucked the algorithm listening to their shite, so I abandoned it a while back and now when I'm looking for new music I use this - you can create a new playlist based on a track you like and it'll push it straight to Spotify: https://magicplaylist.co/. Source: almost 3 years ago

• Hey

  3) A weekly playlist for each one. Only new songs. https://magicplaylist.co/#/pt?_k=4mkq5q (welcome). Source: about 3 years ago