Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Becoming Human

MAY 15, 2023

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

DECEMBER 4, 2024

These languages offer powerful libraries that simplify complex tasks but require a learning curve for those unfamiliar with coding. Data Wrangling The process of cleaning and preparing raw data for analysis—often referred to as “ data wrangling “—is time-consuming and requires attention to detail.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Basic Data Science Terms Familiarity with key concepts also fosters confidence when presenting findings to stakeholders. Below is an alphabetical list of essential Data Science terms that every Data Analyst should know. Data Wrangling: The cleaning, transforming, and structuring of raw data into a format suitable for analysis.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Mathematical Foundations In addition to programming concepts, a solid grasp of basic mathematical principles is essential for success in Data Science. Mathematics is critical in Data Analysis and algorithm development, allowing you to derive meaningful insights from data.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52