IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Machine learning and deep learning are both subsets of AI.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Rocket-Powered Data Science

JULY 6, 2021

The almost forgotten “orphan” in these architectures, Fog Computing (living between edge and cloud), is now moving to a more significant status in data and analytics architecture design. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

Smart Data Collective

JUNE 4, 2021

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Deep Learning.

Data Science 105

Data Science Statistics Deep Learning Machine Learning 105

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 124

Predictive Analytics Analytics Predictive Modeling Data mining 124

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning and data mining tools can be very useful in this regard.

Machine Learning 89

Machine Learning Data mining Advertising Deep Learning 89

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics in business Predictive analytics draws its power from a wide range of methods and technologies, including big data, data mining, statistical modeling, machine learning, and assorted mathematical processes. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Smart Data Collective

APRIL 3, 2020

Big data is driving a number of changes in the business community. Some of the benefits of big data incredibly obvious. However, there are also a lot of other benefits big data creates that don’t get as much publicity. Big Data is the Future of Giveaway Offerings. Chatbots for Giveaways.

Big Data 83

Big Data Data-driven Data mining Software 83

CIO Business Intelligence

MARCH 13, 2024

Altrettanto importante (e forse più trascurata) è la questione dei big data che servono per addestrare i modelli e il costo connesso. L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%).

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

IBM Big Data Hub

DECEMBER 15, 2023

PyTorch is an open-source AI framework offering an intuitive interface that enables easier debugging and a more flexible approach to building deep learning models. It is a popular choice among researchers and developers for rapid software development prototyping and AI and deep learning research. Morgan and Spotify.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

Sisense

APRIL 10, 2020

Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Libraries used for NLP are: NLTK, gensim, SpaCy , glove, and Scikit-Learn. Every library has its own purpose and benefits.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Domino Data Lab

MARCH 11, 2021

Here are several key considerations you should take into account when selecting a machine learning framework for your project. When you start your search for a machine learning framework, ask these three questions: Will you use the framework for deep learning or classic machine learning algorithms?

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

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? In the age of big data, companies are always on the hunt for advanced tools and techniques to extract insights from data reserves.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

FineReport

DECEMBER 19, 2019

Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. In addition, tools for data analysis and data mining are also important. Excel, Python, Power BI, Tableau, FineReport are frequently used by data analysts.

Knowledge Discovery 98

Knowledge Discovery Visualization Reporting Data mining 98

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

Rocket-Powered Data Science

DECEMBER 15, 2018

In deep learning, as in typical neural network models, the method by which those adjustments to the model parameters are estimated ( i.e., for each of the edge weights between the network nodes) is called backpropagation.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

Rocket-Powered Data Science

DECEMBER 16, 2018

They are not machine learning algorithms in themselves, but GAs can be applied across ensembles of machine learning models and tasks, in order to find the optimal model (perhaps globally optimal model) across a collection of locally optimal solutions. Workshop on Meta-Learning (MetaLearn 2018).

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Rocket-Powered Data Science

APRIL 25, 2019

So, I have updated the list, adding some new opportunities, keeping many of the previous ones, and removing the obsolete ones.

Data Science 38

Data Science Machine Learning Deep Learning Statistics 38