Open in app

Sign In

Write

Sign In

Jake Batsuuri
Jake Batsuuri

1K Followers

Home

About

Published in Computronium Blog

·Aug 27, 2021

Text Segmentation

Normalization, Tokenization, Sentence Segmentation + Useful Methods — What does normalizing a text do? We have previously called this method .lower() to turn all of the words lowercase, so that strings like “the” and “The” both become “the”, so we don’t double count them. What if we wanna do even more? Stemming For example we can strip the affixes from words in a process called stemming. …

Language Model

7 min read

Text Segmentation
Text Segmentation
Language Model

7 min read


Published in Computronium Blog

·Aug 25, 2021

Inputting & PreProcessing Text

Input Methods, String & Unicode, Regular Expression Use Cases — NLTK has preprocessed texts. But we can also import and process our own texts. Importing from __future__ import division import nltk, re, pprint To Import a Book as a Txt Install urlopen: !pip install urlopen And: import urllib.request url = "https://www.gutenberg.org/files/11/11-0.txt" raw = urllib.request.urlopen(url).read() type(raw) # <type 'str'>

Naturallanguageprocessing

13 min read

Inputting & PreProcessing Text
Inputting & PreProcessing Text
Naturallanguageprocessing

13 min read


Published in Computronium Blog

·Jul 27, 2021

What are Context Free Languages?

Grammars, Derivation, Expressiveness, Chomsky Hierarchy — Previously, we talked about how languages are studied using the notion of a formal language. Formal language is a mathematical construction that uses sets to describe a language and understand its properties. We introduced the notion of a string, which is a word or sequence of characters, symbols or letters…

Linguistics

10 min read

What are Context Free Languages?
What are Context Free Languages?
Linguistics

10 min read


Jul 19, 2021

Using Lexical Resources Effectively

Frequency Distributions, Wordlists, WordNet, Semantic Similarity — Work in Natural Language Processing typically uses large bodies of linguistic data. In this article, we explore some lexical resources that help us ingest and analyze corpora. These resources are part of Python or the NLTK library. Getting NLTK Corpora We can access pre-imported corpora in NLTK in one of 2 ways: emma…

Naturallanguageprocessing

15 min read

Using Lexical Resources Effectively
Using Lexical Resources Effectively
Naturallanguageprocessing

15 min read


Published in Computronium Blog

·Mar 21, 2021

Language Generation with Recurrent Models

LSTM, Sampling, Smart Code Completion Tool — How Do You Generate Sequence Data? The general way is to train a machine learning model then ask it to predict the next token, whether they be characters or words or n-grams. A model with this predictive capability is called a Language Model. The model is basically learning the latent space i.e. …

Deep Learning

9 min read

Language Generation with Recurrent Models
Language Generation with Recurrent Models
Deep Learning

9 min read


Published in Computronium Blog

·Mar 16, 2021

Language Processing with Recurrent Models

Bidirectional RNNs, Encoding, Word Embedding and Tips — What's a Bidirectional RNN? Bidirectional RNN is an RNN variant, that sometimes can increase performance. It is especially useful for natural language processing tasks. The BD-RNN uses two regular RNNs, one of them where the sequential data is going forward, and one where the data sequences backwards, then merging their representations. This method doesn’t…

Deep Learning

8 min read

Language Processing with Recurrent Models
Language Processing with Recurrent Models
Deep Learning

8 min read


Published in Computronium Blog

·Mar 15, 2021

Recurrent Models Overview

Recurrent Layers: SimpleRNN, LSTM, GRU — What’s SimpleRNN? SimpleRNN is the recurrent layer object in Keras. from keras.layers import SimpleRNN Remember that we input our data point, for example the entire length of our review, the number of timesteps. Now the SimpleRNN processes data in batches, just like every other neural network. …

Deep Learning

7 min read

Recurrent Models Overview
Recurrent Models Overview
Deep Learning

7 min read


Published in Computronium Blog

·Mar 14, 2021

Convolutional Models for Sequential Data

Easing Into Recurrent Neural Networks — Remember these two useful properties of Convolutional Models. Convolutional Models Overview Convolutions, Kernels, Downsampling & Propertiesmedium.com Translation Invariance A convolutional model can learn a certain pattern in the lower right area, then after that point detect it anywhere on the image. Spatial Hierarchy A convolutional model can learn patterns in a hierarchical fashion, much like we do. The…

Deep Learning

7 min read

Convolutional Models for Sequential Data
Convolutional Models for Sequential Data
Deep Learning

7 min read


Published in Computronium Blog

·Mar 7, 2021

Working Understanding of Convolutional Models

Creating, Preprocessing, Data Augmentation, Feature Extraction, Fine Tuning — How to make your own Convolutional Model?

Machine Learning

11 min read

Working Understanding of Convolutional Models
Working Understanding of Convolutional Models
Machine Learning

11 min read


Published in Computronium Blog

·Mar 5, 2021

Convolutional Models Overview

Convolutions, Kernels, Downsampling & Properties — What does a CNN model look like in code? from keras import layers from keras import models seq_model= models.Sequential() seq_model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1))) seq_model.add(layers.MaxPooling2D((2, 2))) seq_model.add(layers.Conv2D(64, (3, 3), activation='relu')) seq_model.add(layers.MaxPooling2D((2, 2))) seq_model.add(layers.Conv2D(128, (3, 3), activation='relu'))

Convolutional Network

8 min read

Convolutional Models Overview
Convolutional Models Overview
Convolutional Network

8 min read

Jake Batsuuri

Jake Batsuuri

1K Followers

I write about software && math. Occasionally I design && code. Find my stuff batsuuri.ca

Following
  • Victor Oschi

    Victor Oschi

  • Scott Galloway

    Scott Galloway

  • Julie Zhuo

    Julie Zhuo

  • Douglas Rushkoff

    Douglas Rushkoff

  • Tim Denning

    Tim Denning

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Text to speech