CIO Business Intelligence

JANUARY 19, 2024

Cost: $180 per exam Location: Online Duration: Self-paced Expiration: Credentials do not expire SAS Certified Advanced Analytics Professional The SAS Certified Advanced Analytics Professional credential validates your ability to analyze big data with a variety of statistical analysis and predictive modeling techniques.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

CIO Business Intelligence

FEBRUARY 10, 2023

Benefits of predictive analytics Predictive analytics makes looking into the future more accurate and reliable than previous tools. Retailers often use predictive models to forecast inventory requirements, manage shipping schedules, and configure store layouts to maximize sales.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

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 118

Predictive Analytics Analytics Predictive Modeling Data mining 118

Decision Management Solutions

JANUARY 16, 2020

executive editor of The Machine Learning Times and founder of the Predictive Analytics World and Deep Learning World conference series, discusses the pitfalls of predictive analytics in his article, “ Why Operationalizing Machine Learning Requires a Shrewd Business Perspective.”

Machine Learning 87

Machine Learning Predictive Modeling Predictive Analytics Deep Learning 87

CIO Business Intelligence

APRIL 25, 2022

The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. Due to the short nature of the course, it’s tailored to those already in the industry who want to learn more about data science or brush up on the latest skills. Remote courses are also available.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Sisense

APRIL 10, 2020

Nowadays text data is huge, so Deep Learning also comes into the picture. Deep learning works well with Big Data sets, and it is based on the concept of our brain cells (neurons), which is the root of the term “Artificial Neural Networks.” Deep Learning models use Keras and Tensorflow API, which are built in Python.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Data Science and Beyond

SEPTEMBER 19, 2016

Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. Causality and experimentation. on KDNuggets).

Data Science 66

Data Science Predictive Modeling Experimentation Deep Learning 66

IBM Big Data Hub

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. Data analytics vs. business analytics. Business analytics is another subset of data analytics.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

bridgei2i

DECEMBER 15, 2021

Imperative to predicting user preferences or interests and suggestions, the recommendation engine market size is projected to reach $12.03 Anticipating Demand through Predictive Modelling on OTT. AI in Recommendation Engines for OTT Platforms. billion by 2025.[1]

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

IBM Big Data Hub

AUGUST 28, 2023

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

O'Reilly on Data

JUNE 18, 2019

Even if we boosted the quality of the available data via unification and cleaning, it still might not be enough to power the even more complex analytics and predictions models (often built as a deep learning model). An important paradigm for solving both these problems is the concept of data programming.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Smart Data Collective

SEPTEMBER 19, 2019

Good synthesizer technology is key to a good TTS system, which requires sophisticated deep learning neural analysis tools. They use various predictive models to enhance the user experience. The back-end uses this information to convert symbolic linguistic representation to sound.

Machine Learning 81

Machine Learning Technology Deep Learning Predictive Modeling 81

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Source: mathworks.com.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

DMBS2

DECEMBER 12, 2017

Machine learning and AI have little relevance to most traditional transactional apps. Predictive modeling is a huge deal in customer-relationship apps. The most advanced organizations developing and using those rely on machine learning. I see no natural barriers to that trend, assuming it holds up on its own merits.

Machine Learning 50

Machine Learning Predictive Modeling Deep Learning Modeling 50

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection. Banks and other financial institutions train ML models to recognize suspicious online transactions and other atypical transactions that require further investigation.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

O'Reilly on Data

DECEMBER 12, 2019

More structured approaches to sensitivity analysis include: Adversarial example searches : this entails systematically searching for rows of data that evoke strange or striking responses from an ML model. Figure 1 illustrates an example adversarial search for an example credit default ML model.

Machine Learning 190

Machine Learning Modeling Testing Risk Management 190

Domino Data Lab

OCTOBER 7, 2020

The accuracy of any predictive model approaches 100%. Property 4: The accuracy of any predictive model approaches 100%. This means models can always be found that predict group characteristic with high accuracy. There should be no model to accurately predict even and odd rows with random data.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

Cloudera

FEBRUARY 16, 2022

The greater our understanding of how a model works, the better we are able to predict what the output will be for a range of inputs or changes to the model’s parameters. Given the complexity of some ML models, especially those based on Deep Learning (DL) Convolutional Neural Networks (CNNs), there are limits to interpretability.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

IBM Big Data Hub

FEBRUARY 14, 2024

AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Cost-Benefit 87

Cost-Benefit Insurance Unstructured Data Machine Learning 87

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 52

Analytics Predictive Modeling KPI Machine Learning 52

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 221

Modeling Machine Learning Predictive Modeling Consulting 221

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 166

Analytics Machine Learning Deep Learning Data Science 166

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

IBM Big Data Hub

DECEMBER 20, 2023

Unsupervised machine learning Unsupervised learning algorithms—like Apriori, Gaussian Mixture Models (GMMs) and principal component analysis (PCA)—draw inferences from unlabeled datasets, facilitating exploratory data analysis and enabling pattern recognition and predictive modeling.

Machine Learning 81

Machine Learning Modeling Deep Learning Predictive Modeling 81

CIO Business Intelligence

MARCH 22, 2023

The new class often uses advanced techniques such as deep learning, natural language processing, and computer vision to analyze and extract insights from the data. It is often used to train machine learning models and protect sensitive data in healthcare and finance.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

DataRobot Blog

DECEMBER 15, 2022

While AI-powered forecasting can help retailers implement sales and demand forecasting—this process is very complex, and even highly data-driven companies face key challenges: Scale: Thousands of item combinations make it difficult to manually build predictive models.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Smart Data Collective

MAY 17, 2021

All that performance data can be fed into a machine learning tool specifically designed to identify certain events, failures or obstacles. Predictive models, estimates and identified trends can all be sent to the project management team to speed up their decisions. That’s also where big data can step in and vastly expand ops.

Big Data 99

Big Data Cost-Benefit IoT Machine Learning 99

Domino Data Lab

APRIL 21, 2021

deep learning) there is no guaranteed explainability. We will go through a typical ML pipeline, where we do data ingestion, exploratory data analysis, feature engineering, model training and evaluation. It is also suitable for online applications, as the scoring function is usually very lightweight.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

O'Reilly on Data

SEPTEMBER 11, 2019

For example, even though ML and ML-related concepts —a related term, “ML models,” (No. Deep learning,” for example, fell year over year to No. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering. 40; it peaked at Strata NY 2018 at No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

MARCH 24, 2020

A bright future would see data preparation and data quality as first-class citizens in the data workflow, alongside machine learning, deep learning, and AI. It will be interesting to see how this space grows and how the tools are adopted. Dealing with incorrect or missing data is unglamorous but necessary work.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346