ODSC - Open Data Science

APRIL 3, 2023

We looked at over 25,000 job descriptions, and these are the data analytics platforms, tools, and skills that employers are looking for in 2023. Excel is the second most sought-after tool in our chart as you’ll see below as it’s still an industry standard for data management and analytics.

Big Data 52

Big Data ETL Data Science Deep Learning 52

Pickl AI

AUGUST 1, 2023

Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data. Data Integration: Combining data from multiple sources to create a unified view for analysis and decision-making.

Big Data 52

Big Data Data Analysis Data Scientist Data Ingestion 52

Viso.ai

APRIL 10, 2024

Pandas is a free and open-source Python data analysis library specifically designed for data manipulation and analysis. It excels at working with structured data, often encountered in spreadsheets or databases. Data cleaning is crucial to ensure the quality and reliability of your analysis.

Data Analysis 52

Data Analysis Python Machine Learning Data Scientist 52

ODSC - Open Data Science

OCTOBER 20, 2023

You’ll use MLRun, Langchain, and Milvus for this exercise and cover topics like the integration of AI/ML applications, leveraging Python SDKs, as well as building, testing, and tuning your work. You’ll cover the integration of LLMs with advanced algorithms in DataGPT, with an emphasis on their collaborative roles in data analysis.

NLP 52

NLP Data Science Machine Learning Data Analysis 52

Pickl AI

JULY 18, 2023

There are different programming languages and in this article, we will explore 8 programming languages that play a crucial role in the realm of Data Science. 8 Most Used Programming Languages for Data Science 1. Python: Versatile and Robust Python is one of the future programming languages for Data Science.

Data Science 52

Data Science Data Scientist Python Business Intelligence 52

Heartbeat

JUNE 12, 2023

This monitoring requires robust data management and processing infrastructure. Data Velocity: High-velocity data streams can quickly overwhelm monitoring systems, leading to latency and performance issues. This analysis can involve analyzing performance metrics such as accuracy, precision, recall, or F1 score over some time.

Machine Learning 98

Machine Learning Data Drift Explainability Data Quality 98

Pickl AI

NOVEMBER 14, 2023

Looking for an effective and handy Python code repository in the form of Importing Data in Python Cheat Sheet? Your journey ends here where you will learn the essential handy tips quickly and efficiently with proper explanations which will make any type of data importing journey into the Python platform super easy.

Python 52

Python Data Analysis Data Science Data Scientist 52

Pragnakalp

APRIL 29, 2024

However, it’s important to note that the context provided also discusses other key aspects of data science, such as Veracity, which deals with the trustworthiness or usefulness of results obtained from data analysis, and the challenges faced in Big Data Analytics, including data quality, validation, and scalability of algorithms.

Deep Learning 59

Deep Learning Big Data LLM Data Science 59

Pickl AI

JANUARY 23, 2024

Data Management Proficient in efficiently collecting and interpreting vast datasets. Programming Proficiency Hands-on experience in Python and R for practical Data Analysis. Business Acumen Holistic understanding bridging raw data to strategic decisions.

Data Scientist 52

Data Scientist Business Intelligence Machine Learning Big Data 52

Pickl AI

JUNE 18, 2023

Hadoop has become a highly familiar term because of the advent of big data in the digital world and establishing its position successfully. The technological development through Big Data has been able to change the approach of data analysis vehemently. But what is Hadoop and what is the importance of Hadoop in Big Data?

Big Data 52

Big Data Machine Learning Data Quality Data Analysis 52

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy.

Data Analysis 126

Data Analysis Business Intelligence Data Science Python 126

Pickl AI

JULY 12, 2023

Data manipulation in Data Science is the fundamental process in data analysis. The data professionals deploy different techniques and operations to derive valuable information from the raw and unstructured data. The objective is to enhance the data quality and prepare the data sets for the analysis.

Data Analysis 52

Data Analysis Data Quality Data Science Python 52

AWS Machine Learning Blog

JUNE 23, 2023

Explore your Snowflake tables in SageMaker Data Wrangler, create a ML dataset, and perform feature engineering. Train and test the models using SageMaker Data Wrangler and SageMaker Autopilot. Use a Python notebook to invoke the launched real-time inference endpoint. Basic knowledge of Python, Jupyter notebooks, and ML.

Auto-complete 75

Auto-complete Auto-classification ML Data Quality 75

Mlearning.ai

AUGUST 10, 2023

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. Section 3: The technical section for the project where Python and pgAdmin4 will be used. Section 4: Reporting data for the project insights. Figure 3: Car Brand search ETL diagram 2.1.

Business Intelligence 52

Business Intelligence ETL Data Analysis Python 52

O'Reilly Media

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3% Developers are learning how to find quality data and build models that work. Many AI adopters are still in the early stages.

Generative AI 108

Generative AI AI AI Data Analysis 108

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. It is essentially a Python library. You can pip install it.

Machine Learning 52

Machine Learning Data Scientist ML Data Science 52

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. It is essentially a Python library. You can pip install it.

Machine Learning 52

Machine Learning Data Scientist ML Data Science 52

DataRobot Blog

DECEMBER 15, 2022

For code-first users, we offer a code experience too, using the AP—both in Python and R—for your convenience. Prepare your data for Time Series Forecasting. Perform exploratory data analysis. Once the data is ready to start the training process, you need to choose your target variable.

Machine Learning 81

Machine Learning AI AI Data Drift 81

Pickl AI

NOVEMBER 6, 2023

Communication and Storytelling: Data Visualization is an effective way to communicate complex data and findings to both technical and non-technical audiences. Visual representations make it easier to convey information, present key findings, and tell compelling stories derived from data. Does data visualization require coding?

Data Scientist 52

Data Scientist Data Science Data Analysis Python 52

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.

Large Language Models 78

Large Language Models LLM Machine Learning Natural Language Processing 78

Pickl AI

MAY 15, 2024

Let’s explore some key challenges: Data Infrastructure Limitations Small-scale Data Analysis tools like Excel might suffice for basic tasks. But as data volume and complexity increase, traditional infrastructure struggles to keep up.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Quality 52

Artificial Corner

JUNE 29, 2023

However, beware of bad data. Nobody Cares About Poor Data Quality Until There Is A Problem Image created by author with Stable Diffusion Data quality can make or break any data-driven initiative. Under normal circumstances, data quality may seem like an afterthought, something for the IT guys to worry about.

Data Quality 52

Data Quality Data Analysis Data Scientist ChatGPT 52

Heartbeat

FEBRUARY 29, 2024

Photo by Nathan Dumlao on Unsplash Introduction Web scraping automates the extraction of data from websites using programming or specialized tools. Required for tasks such as market research, data analysis, content aggregation, and competitive intelligence. Below is a sample Python code.

LLM 52

LLM Data Extraction Metadata Python 52

The MLOps Blog

MAY 9, 2023

The components comprise implementations of the manual workflow process you engage in for automatable steps, including: Data ingestion (extraction and versioning). Data validation (writing tests to check for data quality). Data preprocessing. Model performance analysis and evaluation.

ML 98

ML Machine Learning Metadata Automation 98

Dlabs.ai

DECEMBER 6, 2022

They can help you with: Data quality audits Building data systems and pipelines Custom AI development services Machine learning consulting Beyond their artificial intelligence expertise, the team values its people-centric approach, communicating between themselves and with the client, ensuring every project exceeds expectations.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Computer Vision Machine Learning 52