Using in-memory access in Data Science. A simple performance comparison between disk-based databases and in-memory access
The amounts and throughput of data to be analysed in financial markets data analysis can be daunting. This is by no means specific to the financial world, as it happens in many other data analysis fields too. What is pretty unique to this specific industry is that data is highly structured (something that does not happen so often in other fields). Huge amounts of small size and mostly unrelated data messages is what constitutes financial market data: it is easy to end up with hundreds of millions of small messages to be received, stored, decoded, parsed and correlated.
Analysing such a huge amount of data requires many iterations, and the need of saving time in random data access becomes relevant.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
This post will help you in finding different websites where you can easily get free Datasets to practice and develop projects in Data Science and Machine Learning.
Learn Data Science | How to Learn Data Science for Free. In this post, I have described a learning path and free online courses and tutorials that will enable you to learn data science for free.