This article focus on introducing ML and its use in classification. Mathematical principles have not been covered in it. We will cover some mathematical details and also the basics algorithms in next few articles.
Machine learning in AI has affected many fields specially those which require repetitive tasks such as marketing automation. Manual work conditions are changing rapidly and those who are adopting to change and continuously trying to implement new methods are those who will win eventually.
The program has the potential to create an unparalleled Digital upskilling and re-skilling capability. Overall, the program has uniquely positioned with multi-year and multi-fold benefits.
In this blog, you will learn how to become a Machine Learning Engineer. Also, you will learn about the skills, responsibilities, salary and job trends of ML professionals.
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This is a Leopards team’s submission for the Propaganda Detection datathon. Key findings: the best performing classifier is logistic regression, operating on Word2vec representations of the sentences plus several designed features like the proportion of sentiment-bearing words in the sentence.
Propaganda is a form of communication that is aimed at influencing the attitude of a community toward some cause or position. It often presents facts selectively to encourage a particular synthesis. The disinformation damages the reputation of respectable news outlets, organisations and very bad for business indeed. The objective of the Hackathon is to be able to detect the Propaganda and Non-propaganda news as well as to develop a model that can help with the venture. The other objectives of this work includes detecting phrases which are propagandist and also finding out the type of propaganda it is. The algorithms that we will be taking help from are Passive Aggressive, Multiple Layer Perceptron Network, Logistic Regression, AdaBoost, Decision Tree, Random Forest, KNN, SVM and Naive Bayes to detect the potentially propagandistic and non-propagandistic sentences in a news article. For the evaluation, we are calculating F1 Score to measure the class imbalance in the testing dataset. We have used the best model for detecting propagandist and non-propagandist articles, phrases and also type of propaganda.
Everyday we come across fancy jargon like data science, machine learning , artificial intelligence, computer vision, NLP, etc. You must have wondered as why terms like data science and AI are used together in names of research institutes like the Alan Turing Institute for Data Science and Artificial Intelligence. Does these two words mean the same ? Does it not? If it is same , why not club them into a single term , if not then why not have two different names instead of using them along side one another.
Over the years AI has developed from a theoretical concept to an acceptable technological term that is used in all fields. From self-driven cars, complex medical procedures, welfare, and many other areas. Artificial intelligence was viewed by many as a complex undertaking and was considered as an area for computer geniuses and nerds. However, in […]