When we check the weather forecast or the potential price of plane tickets, we come across information base on Big Data. These are huge amounts of unstructure information. Now there is so much data that it is impossible to collect and process it manually. However, it is still possible to “tame” – this is what a data scientist does. An expert analyzes the data and “trains” an ML model that can identify certain types of patterns. In particular, recognize and classify objects in pictures and videos, recommend products in the online store and friends in social networks. A data scientist not only designs user functions, but also makes useful business preictions. For example, will a new user return to the product.
Each time you have to look for new approaches
The specialist collects data and analyzes the behavior of users with similar characteristics, and then “trains” the model to make a preiction. What do you nee to start? Know several programming languages at least at a basic level. Requires Python (including Tonga B2B List Pandas, Numpy, scikit-learn, LightGBM, CatBoost, TensorFlow) or R, as well as SQL (for working with data). Mention discrete mathematics, statistics and statistical analysis. This knowlege will be neee to analyze data, find patterns and build mathematical models. Understand the basic algorithms of machine learning — logistic regression, decision trees, gradient boosting profession.
Calculations should be made
There are practically no trivial problems in it, and test them. And the first results are really exciting. For example, a classic task for data scientists is to determine AERO Leads which of the Titanic’s passengers survive. on the basis of information from tickets. A traine model can preict the result with 97-98% accuracy,” — Oleksiy Minenko, Data Scientist at Jiji . Have you notice how skillfully Netflix offers you movies and series that you can watch for days and nights? Behind the successful recommendations of the streaming service is the work of a machine learning engineer.
