Analytics Vidhya

MARCH 17, 2023

These sessions cover a wide range of topics, from people analytics and conversational intelligence to deep learning and time series forecasting. Aspiring individuals, students, freshers, current professionals […] The post Upcoming DataHour Sessions to Watch Out For appeared first on Analytics Vidhya.

Deep Learning 318

Deep Learning Forecasting People Analytics Interactive 318

Analytics Vidhya

APRIL 28, 2022

The post An End-to-End Guide on Time Series Forecasting Using FbProphet appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. […].

Forecasting 271

Forecasting Data Science Publishing Analytics 271

Analytics Vidhya

SEPTEMBER 6, 2021

This article was published as a part of the Data Science Blogathon Introduction: Artificial Neural Networks (ANN) are algorithms based on brain function and are used to model complicated patterns and forecast issues. The […]. The post Introduction to Artificial Neural Networks appeared first on Analytics Vidhya.

Deep Learning 318

Deep Learning Forecasting Data Science Publishing 318

Dataiku

OCTOBER 4, 2021

Time series forecasting use cases are certainly the most common time series use cases, as they can be found in all types of industries and in various contexts. Using RNNs & DeepAR Models to Find Out.

Forecasting 138

Forecasting Deep Learning IT Sales 138

Analytics Vidhya

NOVEMBER 1, 2021

Deep learning algorithms can have huge functional uses when provided with quality data to sort through. Diverse fields such as sales forecasting and […]. The post Employee Attrition Prediction – A Comprehensive Guide appeared first on Analytics Vidhya.

Deep Learning 319

Deep Learning Forecasting Sales Data Science 319

Analytics Vidhya

OCTOBER 28, 2020

Overview This article will see how to create a stacked sequence to sequence the LSTM model for time series forecasting in Keras/ TF 2.0. . The post Multivariate Multi-step Time Series Forecasting using Stacked LSTM sequence to sequence Autoencoder in Tensorflow 2.0 / Keras appeared first on Analytics Vidhya.

Forecasting 245

Forecasting Modeling Analytics Deep Learning 245

Analytics Vidhya

OCTOBER 28, 2021

Deep learning algorithms can have huge functional uses when provided with quality data to sort through. Diverse fields such as sales forecasting and […]. The post Beginner’s guide on How to Train a Classification Model with TensorFlow appeared first on Analytics Vidhya.

Modeling 271

Modeling Deep Learning Forecasting Sales 271

Dataiku

DECEMBER 20, 2021

The encoder-decoder framework is undoubtedly one of the most popular concepts in deep learning. Widely used to solve sophisticated tasks such as machine translation, image captioning, and text summarization, it has led to great breakthroughs.

Deep Learning 98

Deep Learning Forecasting IT 98

O'Reilly on Data

FEBRUARY 11, 2019

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. AI and machine learning in the enterprise. Deep Learning. Foundational data technologies.

Big Data 272

Big Data Technology Machine Learning Deep Learning 272

Analytics Vidhya

OCTOBER 28, 2022

Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. The post Non-Generalization and Generalization of Machine learning Models appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Machine Learning 399

Machine Learning Modeling Forecasting Data Science 399

Smart Data Collective

AUGUST 26, 2021

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

Deep Learning 100

Deep Learning Finance Cost-Benefit Advertising 100

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

Smart Data Collective

SEPTEMBER 9, 2019

The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. However, deep learning and other artificial intelligence technologies will also change the future of technical analysis as well. New developments in deep learning with technical analysis.

Deep Learning 92

Deep Learning Forecasting Machine Learning Publishing 92

Analytics Vidhya

JULY 16, 2024

Introduction Assume you are engaged in a challenging project, like simulating real-world phenomena or developing an advanced neural network to forecast weather patterns. Tensors are complex mathematical entities that operate behind the scenes and power these sophisticated computations.

Machine Learning 341

Machine Learning Forecasting Analytics Deep Learning 341

O'Reilly on Data

MAY 21, 2019

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Modernize existing applications such as recommenders, search ranking, time series forecasting, etc.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

Corinium

JUNE 6, 2019

How can advanced analytics be used to improve the accuracy of forecasting? The use of newer techniques, especially Machine Learning and Deep Learning, including RNNs and LSTMs, have high applicability in time series forecasting.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

KDnuggets

DECEMBER 15, 2022

Get more experience by working on web scraping, data analytics, time-series forecasting, machine learning, and deep learning projects.

Data Science 153

Data Science Deep Learning Forecasting Machine Learning 153

Analytics Vidhya

JULY 15, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview of the project: The goal of this project is to forecast. The post Face Key-point Recognition Using CNN appeared first on Analytics Vidhya.

Forecasting 291

Forecasting Data Science Publishing Analytics 291

CIO Business Intelligence

FEBRUARY 6, 2025

Think about it: LLMs like GPT-3 are incredibly complex deep learning models trained on massive datasets. From automating tedious tasks to unlocking insights from unstructured data, the potential seems limitless. But heres the question I keep asking myself: do we really need this immense power for most of our analytics? And guess what?

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Domino Data Lab

APRIL 29, 2021

Deep learning enthusiasts are increasingly putting NVIDIA’s GTC at the top of their gotta-be-there conference list. Three of them were particularly compelling and inspired a new point of view on transfer learning that I feel is important for analytical practitioners and leaders to understand. Deep Learning Trends from GTC21.

Data Science 134

Data Science Deep Learning Modeling Forecasting 134

Dataiku

MARCH 22, 2021

ALMA, the Atacama Large Millimeter /submillimeter Array, is currently the largest radio telescope in the world. The observatory is the result of an international association between Europe (ESO), North America (NRAO), and East Asia (NAOJ) — in collaboration with the Republic of Chile — to get it built with joint intent.

Deep Learning 64

Deep Learning Forecasting IT 64

O'Reilly on Data

JULY 28, 2020

This tradeoff between impact and development difficulty is particularly relevant for products based on deep learning: breakthroughs often lead to unique, defensible, and highly lucrative products, but investing in products with a high chance of failure is an obvious risk.

Marketing 364

Marketing Experimentation Metrics Testing 364

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Before selecting a tool, you should first know your end goal – machine learning or deep learning.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Smart Data Collective

JUNE 4, 2021

Deep Learning. Deep learning is a subset of machine learning that works similar to the biological brain. Use deep learning when the number of variables (columns) is high. Deep learning is used for speech recognition, board games AI, image recognition, and manipulation. Ensembling.

Data Science 133

Data Science Statistics Deep Learning Machine Learning 133

CIO Business Intelligence

FEBRUARY 10, 2023

With the help of sophisticated predictive analytics tools and models, any organization can now use past and current data to reliably forecast trends and behaviors milliseconds, days, or years into the future. Energy: Forecast long-term price and demand ratios. Forecast financial market trends.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

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

SEPTEMBER 23, 2020

One study forecasts that the market will be worth $23.8 Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lake 135

Data Lake Data Warehouse Unstructured Data Big Data 135

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

CIO Business Intelligence

JUNE 2, 2022

Among the hot technologies, artificial intelligence and machine learning — a subset of AI that that makes more accurate forecasts and analysis as it ingests data — continue to be of high interest as banks keep a strong focus on costs while trying to boost customer experience and revenue. Gartner highlights AI trend in banking.

Predictive Analytics 145

Predictive Analytics Technology Analytics Machine Learning 145

Smart Data Collective

OCTOBER 13, 2021

Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields). In forecasting future events. However, there will always be a decisive human factor, at least for a few decades yet. Prescriptive analytics.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

Smart Data Collective

SEPTEMBER 16, 2020

Deep Learning, Machine Learning, and Automation. Not only do you want to ensure that your predictive analytics tools are providing you with an accurate forecast after data preparation, but you also want to determine that you can correlate predictive analytics to your business objectives.

Predictive Analytics 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

Monotonic Deep Lattice Networks Deep learning is a powerful tool when we have an abundance of data to learn from. In this section, we extend the ideas of building monotonic GAMs and lattice models to construct monotonic deep learning models. Other deep learning models can also be written in this form.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Cloudera

JULY 27, 2021

Fitting Prophet models with complex seasonalities for electricity demand forecasting. Streamlit allows us to rapidly build interfaces to our models, and is the end point of several of our AMPs: We can prototype user facing applications, suitable for internal tools, as in Deep Learning for Question Answering.

Data Science 117

Data Science Enterprise Experimentation Machine Learning 117

Cloudera

FEBRUARY 25, 2021

Here’s a preview of what you can leverage with one click in CML: Deep Learning for Anomaly Detection. Apply modern, deep learning techniques for anomaly detection to identify network intrusions. Deep Learning for Image Analysis. Build a semantic search application with deep learning models.

Deep Learning 84

Deep Learning Machine Learning Visualization Forecasting 84

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. You need experience in machine learning and predictive modeling techniques, including their use with big, distributed, and in-memory data sets.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126