In this project I will investigate the basics of Natural Language Processing (NLP) and aim to predict whether a sample of tweets are either positive or negative. This will consist of combining machine learning principles with text.
In this project I will investigate the basics of Natural Language Processing (NLP) and aim to predict whether a sample of tweets are either positive or negative. This will consist of combining machine learning principles with text. I will use mathematics and statistics to get the text in a format that algorithms can understand.
TWEET: “Good morning everyone! Such a beautiful day!!” -> SENTIMENT ANALYSIS (NLP MODEL) -> SENTIMENT: POSITIVE (Label 0)
TWEET: “The food was awful and the waiters rude.” -> SENTIMENT ANALYSIS (NLP MODEL) -> SENTIMENT: NEGATIVE (Label 1)
The objective of this task is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a derogatory or negative sentiment associated with it.
Full tweet texts are provided with their labels for training data.
Mentioned users’ username have been redacted and replaced with @user. The user column will be dropped.
1,600,000 tweets extracted using the twitter api . The tweets have been annotated (0 = negative, 4 = positive) and they can be used to detect sentiment .
Data can be obtained from this kaggle dataset: https://www.kaggle.com/kazanova/sentiment140
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.
Sentimental Analysis Using SVM(Support Vector Machine). Sentimental analysis is the process of classifying various posts and comments of any social media into negative or positive.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
You will discover Exploratory Data Analysis (EDA), the techniques and tactics that you can use, and why you should be performing EDA on your next problem.