Instagram Spam Detector

Another great artificial intelligence project idea for a beginner to try their hands on is an Instagram spam detector. You can leverage the capabilities of machine learning to develop a spam detection model that can distinguish between genuine and spam comments. It’s a useful AI project that you can keep to yourself or develop and sell as a product (yes, that might be too ambitious, but it can work out). For the required dataset, you can either download one from the web or scrape the web and build one on your own. Do whatever you find convenient. Now, there are multiple approaches to accomplishing this beginner-level AI project. One approach is adding keywords for classifying words akin to spam comments. Use N-Gram to provide weightage to words commonly appearing in spam comments. Next, compare them with scrapped comments from the web. Alternatively, you can use cosine similarity or some other distance-based algorithm. Please note that to enhance the performance of the algorithm employed, you need to eliminate punctuation, stop words, and whitespaces from the dataset. You can use a pre-trained model like BERT or ALBERT for superior results. What makes these models powerful is that they consider factors such as coherence and the context of the sentence.