Breakdown: Simplify AI, ML, NLP, Deep Learning, Computer Vision
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Wondered how your phone knows what you’re saying or how Netflix suggests shows you might like? It’s all thanks to some cool tech stuff like machine learning, artificial intelligence (AI), natural language processing (NLP), computer vision etc. Today, we all are surrounded by these terms but what are these exactly?
Did you ever feel lost in these buzzwords? If so, you are not alone!
Let’s break it down and understand it.
Machine learning, artificial intelligence (AI), natural language processing (NLP), and deep learning are all interconnected but represent different aspects and levels of complexity within the field of computer science and data science.
Below is the Venn Diagram showing the relations between all these terms:
Artificial Intelligence (AI):
AI mimics human intelligence in machines, allowing them to tackle tasks like reasoning, problem-solving, learning, perception, and decision-making. It covers a wide range of techniques and applications, including machine learning, robotics, expert systems, natural language processing, and many more. From fig. 1, we can see that it is the super set for all other mentioned technologies.
Machine Learning (ML):
Machine learning is a subset of artificial intelligence that focuses on algorithms and statistical models allowing computer systems to learn from data without being explicitly programmed. improve their performance over time as they are exposed to more data. They can be categorized into supervised learning (using labeled data), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (learning from feedback).
Deep Learning (DL):
Deep learning dives deep into data, mimicking the interconnected neurons of our brain. Deep learning models can automatically discover hierarchical patterns and features from raw data, eliminating the need for manual feature engineering. They excel in tasks such as image recognition, speech recognition, natural language processing etc. but it requires substantial computational resources and large datasets.
Natural Language Processing (NLP):
NLP is a subset of AI that focuses on enabling computers to understand, interpret, and generate human language in a way that is meaningful and contextually relevant. Everything in deep learning related to text data will eventually comes under the umbrella of NLP.
Computer Vision (CV):
Imagine giving eyes to computers! Computer vision lets machines “see” and understand pictures or videos. It’s why cameras can recognize faces or cars can drive themselves safely!
Computer vision enables computers to gain high-level understanding from digital images or videos. It involves tasks such as image recognition, object detection, image segmentation, and image generation.
In conclusion, these technologies are not just buzzwords but the building blocks of our digital future. Machine learning fuels intelligent decision-making, AI strives to match human cognition, deep learning unlocks complex patterns, NLP bridges human-machine communication, and computer vision gives machines the gift of sight. So, next time you see a cool tech gadget or an app doing something amazing, remember it’s all thanks to these clever technologies working behind the scenes.