Topic: skle Goto Github

👇 Here are 5 public repositories matching this topic...

abhishek305 / pybot-a-chatbot-for-answering-python-queries-using-nlp
skle,Pybot can change the way learners try to learn python programming language in a more interactive way. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. We are implementing NLP for improving the efficiency of the chatbot. We will include voice feature for more interactivity to the user. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.The main issue with text data is that it is all in text format (strings). However, the Machine learning algorithms need some sort of numerical feature vector in order to perform the task. So before we start with any NLP project we need to pre-process it to make it ideal for working. Converting the entire text into uppercase or lowercase, so that the algorithm does not treat the same words in different cases as different Tokenization is just the term used to describe the process of converting the normal text strings into a list of tokens i.e words that we actually want. Sentence tokenizer can be used to find the list of sentences and Word tokenizer can be used to find the list of words in strings.Removing Noise i.e everything that isn’t in a standard number or letter.Removing Stop words. Sometimes, some extremely common words which would appear to be of little value in helping select documents matching a user need are excluded from the vocabulary entirely. These words are called stop words.Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form — generally a written word form. Example if we were to stem the following words: “Stems”, “Stemming”, “Stemmed”, “and Stemtization”, the result would be a single word “stem”. A slight variant of stemming is lemmatization. The major difference between these is, that, stemming can often create non-existent words, whereas lemmas are actual words. So, your root stem, meaning the word you end up with, is not something you can just look up in a dictionary, but you can look up a lemma. Examples of Lemmatization are that “run” is a base form for words like “running” or “ran” or that the word “better” and “good” are in the same lemma so they are considered the same.
User: abhishek305
nlp nltk-library python3 tkinter project skle numpy

faisalahmedbijoy / machine-learning-tutorials
skle,pandas matplotlib sklearn
User: faisalahmedbijoy
Home Page: https://www.youtube.com/channel/UCh9nVJoWXmFb7sLApWGcLPQ
mach pan py skle matp kuet

minaee / classifier
skle,
User: minaee
classi classifier knn knn-classifier machine-learning python skle

mkamara2023 / salary-prediction-project
skle,This project aims to predict salaries based on various job-related features using a Random Forest Regressor model on a job dataset.
User: mkamara2023
linear-regression matplotlib mean-square-error pandas predictive-modeling python sckit-learn skle

pgs17 / python_packages
skle,tutorial for data science and ml packages with python
User: pgs17
pandas-python python skle matplotlib-pyplot numpy seaborn keras-neural-networks tensorflow