Why are we suddenly so concerned about data and statistics? The answer lies in the explosion of data generated by institutions, businesses, NGOs, etc.
The Airbus A350 is a good example. According to Flight Safety Australia, the Airbus A350 has 50,000 sensors on board and generates 2.5 terabytes of data per day of operation. Yes, you read that correctly: 50,000 sensors on board and 2.5 terabytes of data per day of operation.
The million-dollar question is: what to do with all this data? Good question, isn’t it? Well, I’m starting a series of articles. Every Saturday, I will publish an article titled “Demystifying Machine Learning,” where we will begin to explore the fundamentals of ML. Later on, we’ll see how data-driven companies like Airbus and many others use machine learning in their daily operations to make informed decisions, discover new hidden patterns in data, and gain valuable insights that help the company minimize costs and maximize gains.
Checkout article already published
- Demystifying Machine Learning - Part I (Introduction)
- Demystifying Machine Learning - Part II (What is holding you back)
- Demystifying Machine Learning - Part III (Understand CRISP-DM in Practice)
- Demystifying Machine Learning - Part IV (Build a model to predict house price)
- Demystifying Machine Learning - Part V (Introduction: How to deploy ML projects)