How to Install Anaconda in Linux Mint!
Author(s): Garima Nishad Originally published on Towards AI. Programming, Systems Too hectic? Not anymore! Go to this link where youβll be able to download the installer provided by βAnaconda Distributionβ https://www.anaconda.com/distribution/ I wanted a Python 3.7 version but you can choose either …
DIM: Learning Deep Representations by Mutual Information Estimation and Maximization
Author(s): Sherwin Chen Originally published on Towards AI. Encoder Network Source: Pixabay This is our second article of the series about mutual information. In the previous articles, we have seen how to maximizes the mutual information between two variables via the MINE …
Tutorial on Data Wrangling: College Towns Dataset
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Data wrangling is the process of converting data from its raw form to the tidy form ready for analysis. Data wrangling is an important step in data preprocessing and includes several processes …
Image Classification using Deep Learning & PyTorch: A Case Study with Flower Image Data
Author(s): Avishek Nag Originally published on Towards AI. Classifying Flower images using Convolutional Deep Neural Network with PyTorch library Photo by Krystina rogers on Unsplash Classifying image data is one of the very popular usages of Deep Learning techniques. In this article, …
How to use the SCP Command for File Transfer
Author(s): Garima Nishad Originally published on Towards AI. Using File Transfer on Linux U+007C Towards AI SCP (secure copy) command in Linux can be confusing, let me make this a bit easier for you In this blog post, Iβm going to show …
Linear Regression Analysis in Materials Sciences
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Parabolic fit of the conduction band of MoS2 crystal. This code performs linear regression on simulated band structure data for MoS2 crystal. The band structure of MoS2 was calculated in a previous …
DIAYN: Diversity Is All You Need
Author(s): Sherwin Chen Originally published on Towards AI. Top highlight Diving Into DIAYN U+007C Towards AI An Unsupervised Information-Based Method to Learn Diverse Skills Different skills learned by DIAYN without any extrinsic reward signal. Source: https://sites.google.com/view/diayn Introduction We discuss an information-based reinforcement …
Several Ways for Machine Learning Model Serving (Model as a Service)
Author(s): Edward Ma Originally published on Towards AI. Using Model as a Service (MaaS) on Cloud Platforms Top highlight Photo by Edward Ma on Unsplash No matter how well you build a model, no one knows it if you cannot ship model. …
@Bayesβ Theorem For Bae
Author(s): Michael Knight Originally published on Towards AI. Intro to Probability and Stats U+007C Towards AI Introduce someone to probability theory and statistics without scaring them off Source Bayesβ Theorem is something that confuses and frustrates many, but is not as awful …
Why Precision and Recall metric?
Author(s): Jalal Mansoori Originally published on Towards AI. What is a Class-imbalanced dataset? Image by Author Before answering the above question let me tell you my experience when I was learning about the evaluation of learning algorithms in classification problems. Currently, I …
Data Science 101 β A Short Course on Medium Platform with R and Python Code Included
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Data Science 101 is intended for individuals that have some prior exposure or knowledge in data science concepts and are interested in practical applications beyond what is offered in most introductory-level data …
EMI: Exploration with Mutual Information
Author(s): Sherwin Chen Originally published on Towards AI. A novel exploration method based on representation learning Source: Photo by Andrew Neel on Unsplash Reinforcement learning could be hard when the reward signal is sparse. In these scenarios, exploration strategy becomes essentially important: …
New Model for Word Embeddings which are Resilient to Misspellings (MOE)
Author(s): Edward Ma Originally published on Towards AI. Photo by Edward Ma on Unsplash Traditional word embeddings are good at solving lots of natural language processing (NLP) downstream problems such as documentation classification and named-entity recognition (NER). However, one of the drawbacks …