Becoming Human

MAY 15, 2023

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. Three of the most popular cloud platforms are Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 12, 2024

Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset. Techniques such as statistical summaries, data visualisation, and correlation analysis help uncover patterns, anomalies, and relationships within the data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Mlearning.ai

JUNE 16, 2023

How to use the Codex models to work with code - Azure OpenAI Service Codex is the model powering Github Copilot. There is a VSCode Extension that enables its integration into traditional development pipelines. The StarCoder Chat provides a conversational experience about programming related topics.

AI 52

AI AI Data Analysis Data Analysis 52

The MLOps Blog

MAY 31, 2023

There can be multiple sources of data at the same time, which can be available in different forms like image, text, and tabular form. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data. How to set up a data processing platform? are present in the data.

ML 59

ML ML Algorithm Machine Learning 59

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Towards AI

JANUARY 22, 2025

The role of a data scientist is changing so fast that often schools cant keep up. Universities still mostly focus on things like EDA, data cleaning, and building/fine-tune models. You have to understand data, how to extract value from them and how to monitor model performances. AWS, Google Cloud, or Azure) is essential.

Data Scientist 105

Data Scientist EDA Exploratory Data Analysis AI 105