ODSC - Open Data Science

DECEMBER 7, 2023

ML Pros Deep-Dive into Machine Learning Techniques and MLOps Seth Juarez | Principal Program Manager, AI Platform | Microsoft Learn how new, innovative features in Azure machine learning can help you collaborate and streamline the management of thousands of models across teams. Check out a few of the highlights from each group below.

Data Science 98

Data Science Data Wrangling Machine Learning Machine Learning 98

Pickl AI

NOVEMBER 4, 2024

Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesis testing, confidence intervals). These concepts help you analyse and interpret data effectively. They introduce two primary data structures, Series and Data Frames, which facilitate handling structured data seamlessly.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

MARCH 20, 2024

Essential technical skills Understanding of statistics and probability A strong foundation in statistics and probability theory forms the bedrock of Data Science. R, with its robust statistical capabilities, remains a popular choice for statistical analysis and data visualization.

Data Science 52

Data Science Data Scientist Data Wrangling Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Understanding its core components is essential for aspiring data scientists and professionals looking to leverage data effectively. Statistics and Mathematics At its core, Data Science relies heavily on statistical methods and mathematical principles. Ensuring data quality is vital for producing reliable results.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Explain the concept of feature engineering in Maachine Learning.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 10, 2023

R’s data manipulation capabilities make cleaning and preprocessing data easy before further analysis. · Statistical Analysis: R has a rich ecosystem of packages for statistical analysis. Most common R Libraries for Data Science In Data Science, you can find several R Libraries and perform different tasks.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

AUGUST 21, 2023

Software engineering concepts facilitate efficient data manipulation, enabling you to design algorithms, create visualizations, and build machine learning models. Step 2: Acquiring Statistical Proficiency A Data Scientist’s toolkit is incomplete without a solid understanding of statistics. Shape your future with us!

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52