Data Science and Machine Learning (Theory and Projects) A to Z - Introduction - Deep learning: Artificial Neural Network

The video discusses the resurgence of deep neural networks (DNN) due to their superior data utilization capabilities compared to traditional machine learning models. It highlights the availability of big data and advanced hardware like GPUs, which make DNNs effective today. The course will cover Python basics, machine learning concepts, and DNNs, using real-world data like the coronavirus dataset for practical learning. Optional videos on the mathematics behind DNNs are also available for interested learners.

What is one of the main reasons for the resurgence of deep neural networks in recent years?

• Lack of traditional algorithms

• Decreased interest in machine learning

• Limited data availability

• Increased computational power

How do deep neural networks compare to traditional machine learning algorithms in terms of data utilization?

• They do not utilize data at all

• They utilize data less efficiently

• They have the same data utilization capacity

• They utilize data more efficiently

Which hardware advancement has significantly contributed to the efficiency of deep neural networks?

• Solid State Drives (SSDs)

• Graphical Processing Units (GPUs)

• Central Processing Units (CPUs)

• Random Access Memory (RAM)

Which library is NOT mentioned as a tool for implementing deep neural networks?

• Scikit-learn

• PyTorch

• Keras

• TensorFlow

Why is Python emphasized as the primary language for this course?

• It is a paid software

• It is the least popular language

• It has great libraries for data handling

• It is not suitable for machine learning

What type of data will be used for practical application in this course?

• Synthetic data

• Real-world coronavirus data

• Simulated weather data

• Historical stock market data

What is the purpose of the optional videos in the course?

• To provide entertainment

• To explain the mathematics behind DNNs

• To offer additional coding exercises

• To discuss unrelated topics