5 Apache Spark Best Practices
Already familiar with the term big data, right? Despite the fact that we would all discuss Big Data, it takes a very long time before you confront it in your career. Apache Spark is a Big Data tool that aims to handle large datasets in a parallel and distributed manner. Apache Spark began as a research project at UC Berkeley's AMPLab, a student, researcher, and faculty collaboration centered on data-intensive application domains, in 2009.
Stop saying "trial and errors" for now: seeing reinforcement learning through some spectrums
Some of you might have got away with explaining reinforcement learning (RL) only by saying an obscure thing like "RL enables computers to learn through trial and errors." But if you have patiently read my articles so far, you might have come to say "RL is a family of algorithms which simulate procedures similar to dynamic programming (DP)."
3 Types of Preventative Maintenance for Data Centers
Image Source: source unsplash.com
Downtime for a data center can be extraordinarily costly — potentially leading to lost…
It’s All About Data: The Training of AI Models
In deep learning, there are different training methods. Which one we use in an AI project depends on the data provided by our customer: how much data is there, is it labeled or unlabeled? Or is there both labeled and unlabeled data?
Buzzword Bingo: Data Science - Teil I
Der im Bereich der Data Science u. a. am häufigsten genutzte Begriff ist derjenige der „Künstlichen Intelligenz“.
6 Faktoren, wie Process Mining Projekte zum Erfolg werden
Nach dutzenden Process Mining Projekten mit unterschiedlichen Rahmenbedingungen gebe ich hier nun sechs handfeste Hinweise, wie Process Mining Projekte generell zum Erfolg werden.
Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning
This article focuses on autonomous trading agent to solve the capital market portfolio management problem. Researchers aim to achieve higher portfolio return while preferring lower-risk actions. It uses deep reinforcement learning Deep Q-Network (DQN) to train the agent.
Wie Maschinen uns verstehen: Natural Language Understanding
Natural Language Understanding (NLU) ist ein Teilbereich von Computer Science, der sich damit beschäftigt natürliche Sprache, also beispielsweise Texte oder Sprachaufnahmen, verstehen und verarbeiten zu können. Das Ziel ist es, dass eine Maschine in der gleichen Weise mit Menschen kommunizieren kann, wie es Menschen untereinander bereits seit Jahrhunderten tun.
Process Mining Camp 2022
Pack your bags, get your provisions, and plan your trip — Just a few more weeks until we get together at this year’s Process Mining Camp on Thursday, 23 June in Eindhoven, the Netherlands.
How to choose the best pre-trained model for your Convolutional Neural Network?
/0 Comments/in Uncategorized /by Mickael KomendyakTransfer Learning refers to the set of methods that allow the transfer of knowledge acquired from solving a given problem to another problem.
Transfer Learning has been very successful with the rise of Deep Learning.
Key Points on AI’s Role In The Future Of Data Protection
/0 Comments/in Artificial Intelligence, Data Security /by Lydia IsehBecause AI can do a lot more than just collect and analyze data — it can also protect it. In this article, we’ll explain what the role of Artificial Intelligence is in the future of data protection.
Ein KI Projekt richtig umsetzen : So geht’s
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category /by Benjamin AunkoferWir von DATANOMIQ und pixolution teilen unsere Erfahrungen aus Deep Learning Projekten, wo es vor allem um die Optimierung und Automatisierung von Unternehmensprozessen rund um visuelle Daten geht, etwa Bilder oder Videos.
Air Quality Forecasting Python Project
/0 Comments/in Data Mining, Data Science, Python, Use Cases /by Shivani PadayaThis project forecast the Carbon Dioxide(Co2) emission levels yearly. Most of the organizations have to follow government norms with respect to Co2 emissions and they have to pay charges accordingly, so this project will forecast the Co2 levels so that organizations can follow the norms and pay in advance based on the forecasted values.
Deep Autoregressive Models
/0 Comments/in Artificial Intelligence, Data Mining, Data Science, Deep Learning, Machine Learning, Main Category /by Sunil YadavIn this blog article, we will discuss about deep autoregressive generative models (AGM). Autoregressive models were originated from economics and social science literature on time-series data where obser- vations from the previous steps are used to predict the value at the current and at future time steps
How to ensure occupational safety using Deep Learning – Infographic
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Insights, Machine Learning, Main Category, Use Cases /by Benjamin AunkoferHow to ensure occupational safety through automatic risk detection using Deep Learning – Infographic
Four essential ideas for making reinforcement learning and dynamic programming more effective
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Predictive Analytics /by Yasuto TamuraThis is the third article of the series My elaborate study notes on reinforcement learning. 1, Some excuses for writing another article on the same topic In the last article I explained policy iteration and value iteration of dynamic programming (DP) because DP is the foundation of reinforcement learning (RL). And in fact this article […]
Deep Generative Modelling
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning /by Sunil YadavNowadays, we see several real-world applications of synthetically generated data, for example solving the data imbalance problem in classification tasks, performing style transfer for artistic images, generating protein structure for scientific analysis, etc. In this blog, we are going to explore synthetic data generation using deep neural networks with the mathematical background.
How Deep Learning drives businesses forward through automation – Infographic
/0 Comments/in Artificial Intelligence, Deep Learning, Machine Learning, Main Category, Use Cases /by Benjamin AunkoferIn cooperation between DATANOMIQ, my consulting company for data science, business intelligence and process mining, and Pixolution, a specialist for computer vision with deep learning, we have created an infographic about a very special use case for companies with deep learning: How to protect the corporate identity of any company by ensuring consistent branding with automated font recognition.
What is Portfolio Risk Management in Python?
/0 Comments/in Python /by Shannon FlynnData science is a crucial industry, with multiple processes today relying on it. One of its more helpful and intriguing applications is in investing, where it helps investors make more informed decisions. Practices like portfolio management in Python help take the guesswork out of this notoriously risky undertaking.