Analytics Vidhya

SEPTEMBER 9, 2021

This article was published as a part of the Data Science Blogathon Introduction Hello everyone, in this article we will pick the use case of sequence modelling, which is time series forecasting. The post Web Traffic Forecasting Using Deep Learning appeared first on Analytics Vidhya.

Deep Learning 316

Deep Learning Forecasting Sales Data Science 316

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.

Deep Learning 245

Deep Learning Forecasting Data Science Publishing 245

Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data Warehouses and Data Lakes in a Nutshell. A Final Word.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

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 167

Forecasting Modeling Analytics Deep Learning 167

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 60

Deep Learning Machine Learning Unstructured Data Modeling 60

CDW Research Hub

JULY 31, 2019

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

IBM Big Data Hub

JANUARY 10, 2024

AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended. For optimal performance, AI models should receive data from a diverse datasets (e.g., The real-world potential of AI is immense.

Unstructured Data 82

Unstructured Data Deep Learning Cost-Benefit Modeling 82