ProjectPro

FEBRUARY 5, 2021

Image classification , a subfield of computer vision helps in processing and classifying objects based on trained algorithms. Image Classification had its Eureka moment back in 2012 when Alexnet won the ImageNet challenge and since then there has been an exponential growth in the field. Table of Contents What is the MNIST dataset?

Datasets 40

Datasets Deep Learning Medical Algorithm 40

ProjectPro

APRIL 2, 2015

Become a Hadoop Developer By Working On Industry Oriented Hadoop Projects When Target statistician Andrew Pole built a data mining algorithm which ran test after test analyzing the data, useful patterns emerged which showed that consumers as a whole exhibit similar purchase behaviors.

Retail 40

Retail Hadoop Big Data Data Mining 40

U-Next

SEPTEMBER 9, 2022

In November 2012, the Apache Software Foundation released Hadoop to the public as Apache Hadoop. . Hadoop is a Java-based Apache open source platform that enables the distributed processing of big datasets across computer clusters using simple programming techniques. MapReduce algorithm is not always the best choice .

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

AltexSoft

OCTOBER 3, 2022

The Google Knowledge Graph saw the world in 2012 and it significantly increased the interest of the academic and business community in the task of representing knowledge in graphs, coining the term “knowledge graph” and setting the trend for the coming years. A knowledge graph example. Knowledge graph example.

Relational Database 52

Relational Database Banking Media Pharmaceutical 52

ProjectPro

MAY 23, 2015

2014 Kaggle Competition Walmart Recruiting – Predicting Store Sales using Historical Data Description of Walmart Dataset for Predicting Store Sales What kind of big data and hadoop projects you can work with using Walmart Dataset? petabytes of unstructured data from 1 million customers every hour. How Walmart uses Big Data?

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

APRIL 12, 2021

Curse of Dimensionality causes lots of difficulties while training a model because it requires training a lot of parameters on a scarce dataset leading to issues like overfitting, large training times, and poor generalization. Autoencoders work great for larger datasets and PCA works well for smaller datasets.

Deep Learning 40

Deep Learning Datasets Machine Learning Algorithm 40

Netflix Tech

DECEMBER 17, 2019

Dump Processing Dumps are needed as transaction logs have limited retention, which prevents their use for reconstituting a full source dataset. Figures 2a and 2b are illustrating the chunk selection algorithm. The watermark algorithm for chunk selection (steps 1 to 4). The watermark algorithm for chunk selection (steps 5–7).

MySQL 79

MySQL PostgreSQL Database Transportation 79

Netflix Tech

DECEMBER 17, 2019

Dump Processing Dumps are needed as transaction logs have limited retention, which prevents their use for reconstituting a full source dataset. Figures 2a and 2b are illustrating the chunk selection algorithm. The watermark algorithm for chunk selection (steps 1–4). The watermark algorithm for chunk selection (steps 5–7).

MySQL 84

MySQL PostgreSQL Database Transportation 84

ProjectPro

JUNE 24, 2021

According to Forbes , in 2012 only 12% of Fortune 1000 companies reported having a CDO (Chief Data Officer). Machine learning and Natural language processing skills : Processing of the data may require algorithms and techniques from the fields of machine learning and natural language processing to be applied. This number grew to 67.9%

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

NOVEMBER 6, 2015

Apache Hive was introduced by Facebook to manage and process the large datasets in the distributed storage in Hadoop. Cloudera Impala was announced on the world stage in October 2012 and after a successful beta run, was made available to the general public in May 2013.

Hadoop 52

Hadoop SQL Java Metadata 52

Knowledge Hut

DECEMBER 28, 2023

Ease of Use: A high-level API enables developers to rapidly construct and train ML models without being concerned with algorithmic details. Scalability: Built to train models on large datasets and distributed systems with scalability in mind. These services enable developers to generate insights and construct intelligent solutions.

Amazon Web Services 64

Amazon Web Services Machine Learning Medical Deep Learning 64

Knowledge Hut

JANUARY 2, 2024

From powering Instagram's backend to enabling advanced machine learning algorithms, Python's vast ecosystem and extensive libraries make it a top choice for varied developmental projects. Prerequisites: Familiarity with object-oriented programming concepts and basic algorithms. Platform: Web, Mobile (Android), Desktop, Servers.

Programming Language 52

Programming Language Programming Java NoSQL 52

AltexSoft

JULY 8, 2021

During the 2012 reelection campaign of Barack Obama, there was a team of data scientists hired to build propensity-to-convert models. Propensity models rely on machine learning algorithms. In one of our articles, we cover the main techniques to prepare datasets for machine learning , so you can check it out for better understanding.

Machine Learning 78

Machine Learning Algorithm Education Data Science 78