Thread for beginners; How to learn machine learning.

Let’s start with something really simple and useful not just for Machine Learning.

Start with a Python library called pandas. It’s a huge library but it's mostly fun for traders because it's kind of rewarding to learn each function and how it gonna affect the way you handle the financial data.

Then learn some basic stuff about Python library called NumPy. Pandas is built on NumPy. Numpy is huge, you just need to understand some basic NumPy functions like NumPy shapes and NumPy arrays

If you understand pandas then you will understand NumPy arrays and shapes easily. Side note: Numpy shapes gonna play an important part in the deep learning model called LSTM - mainly used for time-series analysis(such as financial data) and Natural Language Processing (NLP)

Some thoughts on tick data for long to medium-timeframe trading

1/n

First, let's get the facts straight.
Other timeframe traders (investors) can be visible on micro timeframe data but micro timeframe traders(locals) cannot be visible on other timeframe data(>daily)

So obviously if you have the access then the logical choice is using micro-timeframe data (tick).
Theoretically sounds great but practically if you're hunting for a pattern that goes beyond days or weeks in tick data then it requires huge data to evaluate such patterns.

The workaround is to compress the tick data based on information gain rather than transforming the data based on a fixed timeframe like 1 m 15 minute and then do the evaluation.

Remember the timeframe is just for our convenience so we can read the market induced information. There is no magic timeframe and if it exists then it most likely a curve-fitted one. Ofc that's my own observation and not a ground truth