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browser-based-models-with-tensorflowjs

You may think that machine learning models can only be trained with supercomputers and big data. This first course shows you how you can train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam. deeplearning.ai certificate : https://www.coursera.org/account/accomplishments/records/BURZEBYF8K3A

customers-segmentation

Customer Segmentation Analysis Based on Purchased Products Using the K-Means Method

dissimilarity-matrix

create a dissimilarity matrix from iris dataset using 4 popular distance (euclidean, minkowski, manhattan, supremum)

eda-seaborn

simple exploratory data analysis using seaborn on indonesian teacher dataset

extreme-learning-machine

fcahyo

fictor

An amazing app to find your nearby doctor

food-recognition

gaussnaivebayes

Gauss Naive Bayes in Python From Scratch.

hello-world

first repository

it-cert-automation-practice

Google IT Automation with Python Professional Certificate - Practice files

konversisuhu

latihan-bab1

Latihan Bab 1 Class & Object

naive-bayes-postagger

Implement a unigram based tagger using naive bayes algorithm

nemo

NeMo: a toolkit for conversational AI

numpy-exercise

scrape-news-articles

scraping news articles from Quartz

speechbrain

A PyTorch-based Speech Toolkit

subtitle-cleaner

Remove unimportant information from subtitle with regular expression using python

twitter-sentiment-naive-bayes

Twitter Sentiment Analysis using Naive Bayes

vector-space-model

Information retrieval on articles using vector space models

wine-pattern-recognition

Performing principal component analysis and classifying wine based on their features using naive bayes