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rajneesh8's Projects

artificial-intelligence-word-embedding-by-creating-your-own-short-sentences.- icon artificial-intelligence-word-embedding-by-creating-your-own-short-sentences.-

1.Create **EXACTLY**20 sentences. The maximum length of each sentence is FIVE (5). Two sample sentences may look like: “Excellent work”, “Good students work very hard”.2.Create word embeddings for the vocabulary (i.e. unique words ) in your sentences. You can choose one OR more word embedding methods from the embedding layer approach, the CBOW approach, the Skip-Gram approach, or the GloVe approach.Create a WORD document to answer the following questions for EACH of the word embedding method you choose: 1.Describe your embedding approach, architecture, and all the parameters (i.e. epochs, batches) you used. 2.Describe the dimensionality of your word vectors. 3.List the vocabulary in your training set. 4.Use the t-SNE method to reduce your word vectors to 2-dimension and p lot the 2-D points in a figure . Each point (vector) in the figure MUST be labeled with the original words in your vocabulary. (NOTE: you may need to adjust your training sentences so words with certain meaning cluster closer together in your t-SNE figure) 5.List the training time to train your word embedding model.

machine-learning-clustering-retrieval icon machine-learning-clustering-retrieval

Built text and image clustering models using unsupervised machine learning algorithms such as nearest neighbors, k means, LDA , and used techniques such as expectation maximization, locality sensitive hashing, and gibbs sampling in Python

nlp-1 icon nlp-1

:memo: This repository recorded my NLP journey.

nlp-progress icon nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

nmslib icon nmslib

Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

text-classification-using-word2vec icon text-classification-using-word2vec

perform text classification using a machine learning classification model and combinations of word embeddings or sentence embeddings as a feature vector

text-similarity icon text-similarity

A text similarity computation using minhashing and Jaccard distance on reuters dataset

vector_similarity icon vector_similarity

Python, Java implementation of TS-SS called from "A Hybrid Geometric Approach for Measuring Similarity Level Among Documents and Document Clustering"

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