Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Statistics : Fundamental statistical concepts and methods, including hypothesis testing, probability, and descriptive statistics.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Becoming Human

MAY 15, 2023

In Inferential Statistics, you can learn P-Value , T-Value , Hypothesis Testing , and A/B Testing , which will help you to understand your data in the form of mathematics. It is highly configurable and can integrate with other tools like Git, Docker, and AWS. Things to learn: AWS , GCP , or Microsoft Azure anyone of them.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Scalability Considerations Scalability is a key concern in model deployment.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 25, 2023

Statistical Analysis: Hypothesis testing, probability, regression analysis, etc. Cloud Platforms: AWS, Azure, Google Cloud, etc. Skills and Tools of Data Scientists To excel in the field of Data Science, professionals need a diverse skill set, including: Programming Languages: Python, R, SQL, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

NOVEMBER 27, 2024

Statistical Analysis and Testing R’s rich ecosystem for hypothesis testing, regression modelling, and Bayesian analysis makes it ideal for statistical tasks. These containers ensure consistency and simplify deploying workflows in cloud services like AWS , Google Cloud, or Azure.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure? I have experience working with cloud-based data platforms, such as AWS S3 for data storage, Google BigQuery for data querying, and Azure Machine Learning for deploying machine learning models.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52