ODSC - Open Data Science

AUGUST 15, 2023

Build Classification and Regression Models with Spark on AWS Suman Debnath | Principal Developer Advocate, Data Engineering | Amazon Web Services This immersive session will cover optimizing PySpark and best practices for Spark MLlib. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

Machine Learning 52

Machine Learning Machine Learning Data Science Data Scientist 52

Pickl AI

MARCH 20, 2024

Mastery of statistical concepts equips professionals to make informed decisions and draw accurate conclusions from empirical observations. Proficiency in programming languages Fluency in programming languages such as Python, R, and SQL is indispensable for Data Scientists.

Data Science 52

Data Science Data Scientist Data Wrangling Data Visualization 52

Pickl AI

SEPTEMBER 12, 2024

D Data Mining : The process of discovering patterns, insights, and knowledge from large datasets using various techniques such as classification, clustering, and association rule learning. 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

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

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.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

NoSQL Databases These databases, such as MongoDB, Cassandra, and HBase, are designed to handle unstructured and semi-structured data, providing flexibility and scalability for modern applications. Understanding the differences between SQL and NoSQL databases is crucial for students.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52