Fix a typo in README (explantion → explanation) (#773)

jhaemin · joeyklee · allcontributors[bot] · bomanimc · commit c5f5f9bf0e14 · 2020-03-12T15:44:26.000-04:00
* [nn-refactor] Refactor and reimplementation of NeuralNetwork (#749) * adds temp DiyNeuralNetwork - refactoring NeuralNetwork class * adds updates to refactor * refactoring nn-refactor * adds features for compile and add layers * rm console log * adds train interface * adds basic predict * adds blank functions in data class * update nn class * adds nn compile handling * updates function name * adds data loading functions // todo - clean up * add recursive findEntries function and data loading functions * adds formatRawData function * adds .addData() function * adds saveData function * adds handling for onehot and counting input and output units " " * adds code comments * adds concat to this.meta * changed name to createMetaDataFromData" * adds convertRawToTensors * adds functions for calculating stats * adds normalization and conversion to tensor handling * adds .summarizeData * adds data handling to index * updates summarizeData function to explicitly set meta * updates and adds functions * updates predict function * adds classify() with meta * adds metadata handling and data functions * adds loadData with options in init * adds major updates to initiation and defaults * adds boolean flags to check status to configure nn * adds addData function to index * adds support for auto labeling inputs and outputs for blank nn * code cleanup and function name change * flattens array in cnvertRawToTensors * flattens inputs * flatten array always * adds isOneHotEncodedOrNormalized * updates predict and classify functions and output format * updates param handling in predict and classify * code cleanup * adds save function * code cleanup * adds first pass at loading data * fixes missing isNormalized flag in meta * moves loading functions to respective class * moves files to NeuralNetwork * moves files to NeuralNetwork and rm diyNN * rms console.log * check if metadata and warmedup are true before normalization * adds unnormalize function to nn predict * return unNormalized value * adds loadData() and changes to loadDataFromUrl * adds saveData to index * adds modelUrl to constructor options in index * cleans up predict and classify * fix reference to unNormalizeValue * code cleanup * adds looping to format data for prediction and predictMultiple and classifyMultiple * adds layer handling for options * adds tfvis to index and ml5 root * adds debug flag in options * adds vis and fixes input formatting" " * adds model summary * adds comments and reorders code * refactoring functions with 3 datatypes in mind: number, string, array * adds data handling updates * adds handling tensors * adds process up to training * fixes breaking training * adds full working poc * fix addData check * adds updates to api and notes to fix with functions * adds createMetadata in index * adds image handling in classify functino * adds method to not exceed call stack of min and max * fixes loadData issue * adds first header name for min and max * code cleanup * removes unused functions * fixes setDataRaw * code clean up, organization, and adds method binding to constructor * adds methods to constructor, adds comments, and cleans up * adds methods to constructor for nndata * adds methods to constructor, code cleanup, and organization * docs: add RaisinTen as a contributor (#751) * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] * [neural network] adds first tests for neural network and placeholders (#755) * initial commit for nn test * sets karma testing random to false * adds tests for neuralnetwork class * adds placeholders for tests to do * docs: add LudwigStumpp as a contributor (#758) * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] * fix(Docsify Configuration (docs/index.html)): Use Docsify's auto2top property to reset scroll positi (#761) * docs(feature-extractor.md): Switch the links for regression and classifications p5 editor examples i (#762) * docs: add bomanimc as a contributor (#763) * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] Co-authored-by: Joey Lee <joeyklee@users.noreply.github.com> * fix: typo Co-authored-by: Joey Lee <joeyklee@users.noreply.github.com> Co-authored-by: allcontributors[bot] <46447321+allcontributors[bot]@users.noreply.github.com> Co-authored-by: Bomani Oseni McClendon <bomanimc@gmail.com>
diff --git a/docs/README.md b/docs/README.md
@@ -7,7 +7,7 @@ Welcome to the ml5.js documentation. Here you'll find everything you need to get
 
 Take a ride on the Coding Train to watch Dan Shiffman's ["A Beginner's Guide to Machine Learning with ml5.js"](https://www.youtube.com/watch?v=jmznx0Q1fP0). Here Dan explains what ml5.js is and where it all comes from.
 
-ml5.js is machine learning _for the web_ in your web browser. Through some clever and exciting advancements, the folks building [TensorFlow.js](https://www.tensorflow.org/js) figured out that it is possible to use the web browser's built in graphics processing unit (GPU) to do calculations that would otherwise run very slowly using central processing unit (CPU). A really nice explantion of what is happening with GPUs can be found [here - Why are shaders fast?](https://thebookofshaders.com/01/). ml5 strives to make all these new developments in machine learning on the web more approachable for everyone.
+ml5.js is machine learning _for the web_ in your web browser. Through some clever and exciting advancements, the folks building [TensorFlow.js](https://www.tensorflow.org/js) figured out that it is possible to use the web browser's built in graphics processing unit (GPU) to do calculations that would otherwise run very slowly using central processing unit (CPU). A really nice explanation of what is happening with GPUs can be found [here - Why are shaders fast?](https://thebookofshaders.com/01/). ml5 strives to make all these new developments in machine learning on the web more approachable for everyone.
 
 
 ### Quickstart
