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Destiny Young
Destiny Younghttp://linktr.ee/youngdestinya
Destiny Young is a highly credentialed information technology professional with over 13 years of industry experience. An HND/BSc (Hons) Computer Science graduate. He holds a Master of Technology degree in Information Technology from the prestigious University of South Africa (UNISA). He is a Distinction-grade MBA alumnus of Nexford University, Washington, DC, where he also obtained a First-class MSc degree in Digital Transformation. He is currently pursuing MSc in Cybersecurity. His professional development direction is in Cybersecurity, Digital Transformation, and Business Intelligence. He is a member of the British Computer Society (BCS), the Chartered Institute of Administration of Nigeria (CIA), the Nigeria Computer Society (NCS), etc.

AI refers to the mechanism of incorporating human intelligence into machines through algorithms. It’s a combination of “Artificial” (something made by humans or non-natural) and “Intelligence” (the ability to understand or think). Focus: AI aims to mimic human behaviour by enabling machines to learn, reason, and self-correct.

Examples: 1. Natural Language Processing (NLP): AI-powered chatbots, language translation, and sentiment analysis.

2. Computer Vision: Facial recognition, object detection, and image classification.

3. Expert Systems: Medical diagnosis, financial planning, and recommendation engines. #AI

Machine Learning (#ML) allows systems (computers) to learn automatically from experiences without explicit programming. It’s a subset of AI. Process: ML algorithms make observations on data, identify patterns, and improve decision-making based on examples.

Examples:

1. Regression: Predicting house prices based on features like area, location, and number of bedrooms.

2. Classification: Spam email detection, disease diagnosis, and sentiment analysis.

3. Clustering: Grouping similar customers for targeted marketing.

Deep learning (DL) is a subfield of ML that uses neural networks (inspired by the human brain) to mimic brain-like behaviour.

Characteristics:

1. Neural Networks: DL algorithms work with large neural networks, often with multiple layers.

2. Self-Administered Prediction: DL models analyze vast datasets and provide outputs autonomously.

Examples:

1. Image Recognition: Convolutional Neural Networks (CNNs) for identifying objects in images.

2. Natural Language Processing: Recurrent Neural Networks (RNNs) for language modeling and translation.

3. Autonomous Vehicles: DL powers self-driving cars by processing sensor data.

Destiny Young
Destiny Young is a highly credentialed information technology professional with over 13 years of industry experience. An HND/BSc (Hons) Computer Science graduate. He holds a Master of Technology degree in Information Technology from the prestigious University of South Africa (UNISA). He is a Distinction-grade MBA alumnus of Nexford University, Washington, DC, where he also obtained a First-class MSc degree in Digital Transformation. He is currently pursuing MSc in Cybersecurity. His professional development direction is in Cybersecurity, Digital Transformation, and Business Intelligence. He is a member of the British Computer Society (BCS), the Chartered Institute of Administration of Nigeria (CIA), the Nigeria Computer Society (NCS), etc.
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