CIO Business Intelligence

APRIL 12, 2024

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer.

Deep Learning 124

Deep Learning IT Machine Learning IoT 124

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. There won’t be any need for them.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

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 167

Analytics Machine Learning Data Science Data Collection 167

Smart Data Collective

AUGUST 6, 2020

At Smart Data Collective, we have talked about a few impressive technological trends that are shaping modern business in the 21st-century. You can use deep learning technology to replicate a voice that your audience will resonate with. Marketers should leverage deep learning and other big data tools in every way possible.

Deep Learning 117

Deep Learning Visualization Data-driven Marketing 117

Smart Data Collective

APRIL 24, 2020

It’s impossible to deny the importance of data in several industries, but that data can get overwhelming if it isn’t properly managed. The problem is that managing and extracting valuable insights from all this data needs exceptional data collecting, which makes data ingestion vital.

Data Lake 131

Data Lake Data Collection Deep Learning Management 131

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 279

Machine Learning Data Quality Statistics Modeling 279

CIO Business Intelligence

APRIL 25, 2022

It’s a fast growing and lucrative career path, with data scientists reporting an average salary of $122,550 per year , according to Glassdoor. Here are the top 15 data science boot camps to help you launch a career in data science, according to reviews and data collected from Switchup. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Smart Data Collective

DECEMBER 1, 2022

As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. Each of these trends will continue to shape the way companies use data in the coming years.

Big Data 145

Big Data Internet of Things Data-driven Deep Learning 145

Rocket-Powered Data Science

MAY 21, 2024

To see this, look no further than Pure Storage , whose core mission is to “ empower innovators by simplifying how people consume and interact with data.” In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g.,

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

O'Reilly on Data

MARCH 31, 2020

That foundation means that you have already shifted the culture and data infrastructure of your company. If you’re just learning to walk, there are ways to speed up your progress. Here are some great places to start: “ Rules of Machine Learning: Best Practices for ML Engineering” (Google). Insight Fellows Data PM Program.

Management 363

Management Machine Learning Experimentation Metrics 363

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

CIO Business Intelligence

DECEMBER 15, 2023

Traffic optimization: Using data collected from cameras and road sensors, AI-enabled edge systems can adjust traffic patterns across an entire city in real-time to streamline traffic, optimize public transportation routes, and make roads safer.

Testing 96

Testing Deep Learning Optimization Data Collection 96

Smart Data Collective

APRIL 25, 2022

Artificial intelligence can use deep learning as a means to create automatically generate content for their social media page. Employees will no longer need to worry about carrying out the tasks that they will have had to do previously in an effort to build on their business’ social presence. The Creation of Content on Social Media.

Management 144

Management Machine Learning Marketing Deep Learning 144

Cloudera

NOVEMBER 19, 2020

Analyzing historical data is an important strategy for anomaly detection. The modeling process begins with data collection. Here, Cloudera Data Flow is leveraged to build a streaming pipeline which enables the collection, movement, curation, and augmentation of raw data feeds.

Machine Learning 119

Machine Learning Data-driven Modeling Deep Learning 119

CIO Business Intelligence

MARCH 30, 2022

The company next plans to explore new technologies, such as deep learning, Baumhof says. So, in addition to incorporating new data into your decision intelligence strategy, rethinking the underlying algorithms can also help increase the quality of your results. Augment complex processes — especially for data collection.

Machine Learning 144

Machine Learning Testing Risk Data Collection 144

CIO Business Intelligence

FEBRUARY 10, 2023

Its flagship tool, Pipe Sleuth, uses an advanced, deep learning neural network model to do image analysis of small diameter sewer pipes, classify them, and then create a condition assessment report.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Smart Data Collective

MAY 8, 2022

Let’s not forget that big data and AI can also automate about 80% of the physical work required from human beings, 70% of the data processing, and more than 60% of the data collection tasks. From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace.

Big Data 122

Big Data Data Analytics Analytics Statistics 122

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The global commercial drone market is projected to grow from USD 8.15

Data Collection 76

Data Collection Visualization Data-driven Unstructured Data 76

Decision Management Solutions

FEBRUARY 8, 2021

The goal is to establish the Mayflower 400 as an open platform for marine research that would reduce costs and ease the burden on scientists and sailors, who have to brave a dangerous and unpredictable environment in the course of their data-collecting missions.

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

Cloudera

FEBRUARY 4, 2019

With the rise of streaming architectures and digital transformation initiatives everywhere, enterprises are struggling to find comprehensive tools for data management to handle high volumes of high-velocity streaming data. He currently works at Cloudera, managing their Data-in-Motion product line.

IoT 73

IoT Prescriptive Analytics Internet of Things Digital Transformation 73

IBM Big Data Hub

NOVEMBER 14, 2023

Data products and data mesh Data products are assembled data from sources that can serve a set of functional needs that can be packaged into a consumable unit. Each data product has its own lifecycle environment where its data and AI assets are managed in their product-specific data lakehouse.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

IBM Big Data Hub

APRIL 22, 2024

The US City of Atlanta , for example, uses IBM data collection, machine learning and AI to monitor public transit tunnel ventilation systems and predict potential failures that could put passengers at risk. This will help advance progress by optimizing resources used.

IoT 77

IoT Internet of Things Cost-Benefit Reporting 77

IBM Big Data Hub

MARCH 27, 2024

Some companies attempt to estimate Scope 3 emissions by collecting data from suppliers and manually categorizing data, but progress is hindered by challenges such as large supplier base, depth of supply chains, complex data collection processes and substantial resource requirements.

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

bridgei2i

MARCH 9, 2021

Machine Learning: Since intelligence without learning isn’t intelligence, this subset of AI focuses on parsing data and modifying itself without human effort. ML techniques provide better data-based outputs over time. Deep Learning: DL falls under ML, but its capabilities aren’t comparable.

Technology 52

Technology Deep Learning Data-driven Machine Learning 52

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. training data”) show the tangible outcomes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

DataRobot

OCTOBER 20, 2021

The flow of data through an organization: Mapping how data flows through an organization helps organizations get and stay aligned on potential bias risks with data collection and data degradation. rule-based AI , machine learning , deep learning , etc.)

Machine Learning 52

Machine Learning Metrics Deep Learning Risk 52

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

Cloudera

FEBRUARY 16, 2022

We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle. So, we have workspaces, projects and sessions in that order.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

CIO Business Intelligence

SEPTEMBER 22, 2022

“Data is at the core of digital transformation, and data ingestion, transmission, storage, and analysis are key steps,” says Chen “Huawei provides full-stack data collection, transmission, storage, computing, and analysis solutions to effectively support end-to-end closed-loop data processing.”.

Technology 52

Technology Digital Transformation Broadcasting Uncertainty 52

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 78

Marketing Technology Advertising Machine Learning 78

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

Ontotext

DECEMBER 15, 2023

The official (first) repo is tensorflow/tensor2tensor that has topics: machine-learning reinforcement-learning deep-learning machine-translation tpu. By exploring the first topic machine-learning , we find 117k Github repos. The taxonomy integrates various data sources, offering a holistic view of AI innovation.

Machine Learning 69

Machine Learning Deep Learning Interactive Statistics 69

DataRobot Blog

JULY 27, 2022

Here we will demonstrate an end-to-end unattended workflow that: trains a new model on the Fashion MNIST Dataset uploads it to an Algorithmia Data Collection creates a new algorithm on Algorithmia creates DataRobot deployment Links everything together via the MLOps Agent. The Demo: Autoscaling with MLOps.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. One-fifth use reinforcement learning.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

IBM Big Data Hub

AUGUST 28, 2023

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Marketing and sales: Conversational AI has become an invaluable tool for data collection. It assists customers and gathers crucial customer data during interactions to convert potential customers into active ones.

Enterprise 95

Enterprise Interactive Data-driven Key Performance Indicator 95