IBM Big Data Hub

AUGUST 15, 2022

Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. Model risk management.

Data mining 62

Data mining Risk Modeling Risk Management 62

O'Reilly on Data

JANUARY 22, 2019

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 134

Modeling Finance Uncertainty Data mining 134

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

Deep Learning 70

Deep Learning Experimentation Machine Learning Risk 70

FineReport

MARCH 24, 2024

Data analysts interpret data using statistical techniques, develop databases and data collection systems, and identify process improvement opportunities. They should possess technical expertise in data models, database design, and data mining, along with proficiency in reporting packages, databases, and programming languages.

Statistics 52

Statistics Data mining Visualization Reporting 52

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? For instance, a parsing model could identify the subject, verb and object of a complete sentence. You may need to iterate this process until the results are satisfactory.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

Smart Data Collective

MAY 8, 2022

Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning. With the evolution of technology and the introduction of Hadoop, Big Data analytics have become more accessible. Innovations.

Big Data 104

Big Data Data Analytics Analytics Cost-Benefit 104

Smart Data Collective

SEPTEMBER 21, 2022

Unfortunately, they also have challenges, such as choosing the right business model for their AI startup. As far as Data Analysis is concerned, potential employees should have an extensive knowledge of quantitative research, quantitative reporting, compiling statistics, statistical analysis, data mining, and big data.

Statistics 84

Statistics Software Data mining Marketing 84