Learning and working on Machine learning was something I have been planning for a long time and that was when I got a project which included ML and with the excitement, I was into the project without any prior knowledge or mentorship for ML.
I went through a lot of docs videos to understand the concept of machine learning. here I would like to share with you the confusions and misunderstanding which I had when started with ML.
Before starting with ML the first question I had in my mind was what is the difference between Machine learning, Artificial Intelligence, Neural Networks and Deep Learning.
AI is a process of making computers think. AI is a concept which started in early 1950.AI is a very broad area. The subsets of AI are machine learning, Deep Learning and Data science.
ML is a set of statistical tools to learn from data. It makes data-driven decisions to carry out the task.ML has a certain set of algorithms which would understand a dataset and learn from it. The Initial phase of ML revolves around training a dataset and learning from it to handle new data.
Data science is about understanding data. Data science is used for fetching the data which would be necessary for an AI or ML process.DS handles the visualization of data.
Deep Learning is an advanced concept of machine learning which imitates the human brain. Imitate in the sense, the machines can perform tasks requiring human intelligence. Deep learning is widely used for solving problems like image and voice recognition, self-driving vehicles etc.