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Machine Learning

A collection of 10 posts

Best Machine Learning Books (Updated for 2020)
Machine Learning

Best Machine Learning Books (Updated for 2020)

The list of the best machine learning & deep learning books for 2020.

  • Alessio Gozzoli
    Alessio Gozzoli
28 min read
Distilling knowledge from Neural Networks to build smaller and faster models
Deep Learning

Distilling knowledge from Neural Networks to build smaller and faster models

This article discusses GPT-2 and BERT models, as well using knowledge distillation to create highly accurate models with fewer parameters than their teachers

  • Alex Amadori
    Alex Amadori
27 min read
Naïve Bayes for Machine Learning – From Zero to Hero
Data Science

Naïve Bayes for Machine Learning – From Zero to Hero

Bayes’ Theorem is about more than just conditional probability, and Naive Bayes is a flavor of the theorem which adds to its complexity and usefulness.

  • Anand Venkataraman
    Anand Venkataraman
16 min read
When Not to Choose the Best NLP Model
Deep Learning

When Not to Choose the Best NLP Model

The world of NLP already contains an assortment of pre-trained models and techniques. This article discusses how to best discern which model will work for your goals.

  • Cathal Horan
    Cathal Horan
15 min read
N-Shot Learning: Learning More with Less Data
Deep Learning

N-Shot Learning: Learning More with Less Data

Is it possible to use machine learning with small data? Yes, it is! Here's N-Shot Learning.

  • Heet Sankesara
    Heet Sankesara
15 min read
Gated Recurrent Unit (GRU) With PyTorch
Deep Learning

Gated Recurrent Unit (GRU) With PyTorch

The Gated Recurrent Unit (GRU) is the newer version of the more popular LSTM. Let's unveil this network and explore the differences between these 2 siblings.

  • Gabriel Loye
    Gabriel Loye
19 min read
Becoming One With the Data
Deep Learning

Becoming One With the Data

This article discusses effective ways of handling the data in machine learning projects.

  • Sayak Paul
    Sayak Paul
29 min read
How to plan and execute your ML and DL projects
Deep Learning

How to plan and execute your ML and DL projects

This article gives the readers a checklist to structure their machine learning (applies to deep ones too) projects in effective ways.

  • Sayak Paul
    Sayak Paul
18 min read
A Gentle Introduction to Text Summarization in Machine Learning
Machine Learning

A Gentle Introduction to Text Summarization in Machine Learning

Text summarization is a common problem in the fields of machine learning and natural language processing (NLP). In this article, we'll explore how to create a simple extractive text summarization algorithm.

  • Alfrick Opidi
    Alfrick Opidi
14 min read
Introduction to Anomaly Detection in Python
Machine Learning

Introduction to Anomaly Detection in Python

Learn what anomalies are and several approaches to detect them along with a case study.

  • Sayak Paul
    Sayak Paul
24 min read
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