Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Becoming Human

MAY 15, 2023

In programming, You need to learn two types of language. One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. There is one Query language known as SQL (Structured Query Language), which works for a type of database. Why do we need databases?

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data.

Data Science 130

Data Science Data Scientist ML ML 130

Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results.

ML 110

ML ML Machine Learning Machine Learning 110

Pickl AI

NOVEMBER 28, 2024

Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible. Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. databases, CSV files).

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. They possess a deep understanding of statistical methods, programming languages, and machine learning algorithms. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

MAY 29, 2024

Python excels in general-purpose programming and Machine Learning , while R is highly effective for statistical analysis. SQL is indispensable for database management and querying. Machine Learning Algorithms Understanding and implementing Machine Learning Algorithms is a core requirement.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52