Keras Reviews and details

Social recommendations and mentions

• 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 / 5 days 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 / 14 days 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 / 10 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: 12 months 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 / about 1 year ago

• DO YOU YAML?

  If you’re looking for further resources on running TensorFlow and Keras on a newer MacBook, I recommend checking out this YouTube video: How to Install Keras GPU for Mac M1/M2 with Conda. - Source: dev.to / over 1 year ago

• 65 Blog Posts to Learn Data Science

  Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use Keras and Supervisely for this problem. This guide is for anyone who is interested in using Deep Learning for text recognition in images but has no idea where to start. - Source: dev.to / over 1 year ago

• Keras vs Tensorflow vs Pytorch for a Final year Project

  E.g. If you consider it image classification (you already have the pedestrians extracted and just need to classify their intent), you might find that easier to do with Keras, just butcher one of the examples on keras.io. You might also find fast.ai more to your liking. Source: over 1 year ago

• How to Build a Machine Learning Recommendation Engine w/ TensorFlow & HarperDB

  This is where machine learning takes over. Using libraries such as TensorFlow Recommenders with Keras models, it's easy to shape the data in ways that will allow the items and users to be viewed and compared in a multidimensional perspective. Qualitative features such as item categories and user profile attributes can be mapped into mathematical concepts that can be quantitatively compared with one another,... - Source: dev.to / over 1 year ago

• Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)

  Keras – An open-source software library that provides a Python interface to TensorFlow for artificial neural networks. - Source: dev.to / over 1 year ago

• Speech and facial recognition machine learning algorithm unification problem.

  If this is a personal project, there are freely available libraries, paper implementations etc. That are also available. In the Google results, I see a link from paperswithcode and keras.io. Source: almost 2 years ago

• How to build FPGA-based ML accelerator?

  I would check out hls4ml. It's an open source project made by/for people at CERN to convert neural networks created in Python using QKeras (a quantization extension of Keras) into HLS, with Vivado HLS being the most well supported. There are some caveats though, and a fellow student and I have had trouble getting the generated HLS to match the Keras model and be feasible to synthesize, but it seems to work well... Source: almost 2 years ago

• Negative dimension size caused by subtracting 3 from 1 for 'Conv2D'

  I'm using Keras with Tensorflow as backend , here is my code:. Source: about 2 years ago

• 20+ Free Tools & Resources for Machine Learning

  Keras Keras is an API for neural networks that helps doing quick research. - Source: dev.to / about 2 years ago

• Installing Python3 in Linux

  According to IBM, Artificial Intelligence (AI) is technology that instructs computers to mimic the human mind in decision-making and problem-solving. Machine Learning (ML) is a subset of AI that consist of procedures that leverage on mathematical data models and algorithms to make predictions. Python implements ML and AI with generally fewer lines of code and pre-built libraries and being a scientific language... - Source: dev.to / about 2 years ago

• How to build your own chatbot NLP engine

  At the core of the Xatkit NLU engine we have a Keras/Tensorflow model. - Source: dev.to / about 2 years ago

• [P] keras-genetic: Train Keras Models Using Genetic Algorithms

  Hey r/machinelearning! Recently when working on a WorldModels implementation for keras.io I realized that I needed a genetic algorithm implementation to train the "controller" module. Instead of writing a one off solution, I decided to write Keras Genetic, a full package to train keras models using genetic algorithms. Source: about 2 years ago

• 5 ways to keep your skills fresh after finishing a coding bootcamp

  One way to improve your projects and coding skills is to try new models and libraries. For example, if you did classification with logistic regression, try also with random forest; if you used Tensorflow, now try Keras; if you scraped a website with BeautifulSoup, now do it with Scrapy. You get the point. - Source: dev.to / over 2 years ago

• Data Science toolset summary from 2021

  Keras - Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library. Link - https://keras.io/. - Source: dev.to / over 2 years ago

• Top 10 Python Libraries for Machine Learning

  Website: https://keras.io/ Github Repository: https://github.com/keras-team/keras Developed By: various Developers, initially by Francois Chollet Primary purpose: Focused on Neural Networks. - Source: dev.to / over 2 years ago

• [D] Getting Started

  I also recommend trying to understand the software that's being built by the machine learning class. If you want to build your own machine learning software, check out Keras (http://keras.io/) and the machine learning API's that Keras provides. Source: over 2 years ago