Cloud Best Google Colab Alternatives in 2021 Google Colab is a popular choice for GPU-backed Jupyter notebooks. That being said, it's not without its shortcomings.
Keras The Absolute Guide to Keras In this article, we will dive deeper into the world of TensorFlow and Keras. If you haven't already, I would highly recommend first checking out my previous article, The Absolute
TensorFlow The Absolute Guide to TensorFlow TensorFlow is one of the most popular deep learning libraries of the modern era. Developed by Google and released in 2015, TensorFlow is considered to be one of the best
Optimization How to Use Maximum Likelihood Estimation for Parametric Classification Methods In some previous tutorials that discussed how Bayes' rule works, a decision was made based on some probabilities (e.g. the likelihood and prior). Either these probabilities were given explicitly
Data Science Introduction to Time Series Forecasting: Regression and LSTMs In the first part of this series, Introduction to Time Series Analysis, we covered the different properties of a time series, autocorrelation, partial autocorrelation, stationarity, tests for stationarity, and seasonality.
Data Science Introduction to Time Series Forecasting: Autoregressive Models & Smoothing Methods In Part 1 of this series we looked at time series analysis. We learned about the different properties of a time series, autocorrelation, partial autocorrelation, stationarity, tests for stationarity, and
Announcement Gradient Notebooks just got the biggest update since 2019 We've had an extremely busy start to the year at Paperspace and we're excited to start sharing a number of the things we've been working on. The first one up
Reinforcement Learning Getting Started With OpenAI Gym: Creating Custom Gym Environments This post covers how to implement a custom environment in OpenAI Gym. As an example, we implement a custom environment that involves flying a Chopper (or a helicopter) while avoiding obstacles mid-air.
Machine Learning Introduction to Time Series Analysis Time series analysis and forecasting have many applications: analyzing the sales of your retail chains, finding anomalies in the traffic you're getting to your servers, and predicting stock markets, to
Reinforcement Learning The Machine Learning Practitioner's Guide to Reinforcement Learning: Overview of the RL Universe In this post, we describe the anatomy of how most Deep Reinforcement Learning algorithms work. We also cover the motivation to use RL over standard machine learning, On-Policy v/s Off-Policy learning, the Exploration-Exploitation Tradeoff, and many more important RL concepts.
Reinforcement Learning The Machine Learning Practitioner's Guide to Reinforcement Learning: All About Markov Decision Processes Deep Reinforcement Learning is one of the most quickly progressing sub-disciplines of Deep Learning right now. In less than a decade, researchers have used Deep RL to train agents that
RNN Advanced Recurrent Neural Networks: Bidirectional RNNs This series gives an advanced guide to different recurrent neural networks (RNNs). You will gain an understanding of the networks themselves, their architectures, their applications, and how to bring the models to life using Keras.
RNN Advanced Recurrent Neural Networks: Deep RNNs This series gives an advanced guide to different recurrent neural networks (RNNs). You will gain an understanding of the networks themselves, their architectures, applications, and how to bring the models
Object Detection How to Train a Scaled-YOLOv4 Object Detection Model In this blog, we will show an example of how to train and generalize Scaled-YOLOv4 on your custom dataset to detect custom objects.
Reinforcement Learning Getting Started With OpenAI Gym: The Basic Building Blocks In this article, we'll cover the basic building blocks of Open AI Gym. This includes environments, spaces, wrappers, and vectorized environments.
Reinforcement Learning A Thorough Introduction to Reinforcement Learning Access to humongous amounts of data and the availability of enormous computational power have led us to explore various techniques to draw out useful patterns and lead better lives. Churning
Machine Learning Top AI Artists You Should Be Following in 2021 Take a look at this list of top AI artists and explore how each artist integrates AI into their work and respective mediums in this new and exciting era of collaboration.
Computer Vision Build A Flask Web App To Compress Images Using A Variational Autoencoder In this tutorial, we'll build a web application using Flask which will allow the user to upload images to be encoded (i.e., compressed) using a pre-trained variational autoencoder (VAE)
Machine Learning How to Apply Bayesian Decision Theory in Machine Learning In a previous article we discussed the theory behind Bayesian Decision Theory in detail. In this article we'll see how to apply Bayesian Decision Theory to different classification problems. We'll
Machine Learning Bayesian Decision Theory Explained Bayesian Decision Theory is the statistical approach to pattern classification. It leverages probability to make classifications, and measures the risk (i.e. cost) of assigning an input to a given
Tutorial How to Train A Question-Answering Machine Learning Model (BERT) In this article, I will give a brief overview of BERT based QA models and show you how to train Bio-BERT to answer COVID-19 related questions from research papers.
Announcement New! Console redesign We are super excited to launch the newest console redesign to all users starting today. The Paperspace web console is the primary way that tens of thousands of developers interact
Research Data For Justice Resources Whether you are a Data Scientist, ML Engineer, Activist, or just a Human who feels the call to contribute, we hope you find inspiration, or even your next move, in the resources below.
TensorFlow Paperspace Joins TensorFlow AI Service Partners We're excited to announce that we've partnered with the TensorFlow team as an official AI service Partner. As one of the world's most popular open source machine learning frameworks, with
Keras How To Train Keras Models Using the Genetic Algorithm with PyGAD PyGAD is an open-source Python library for building the genetic algorithm and training machine learning algorithms. It offers a wide range of parameters to customize the genetic algorithm to work
