Analytics Vidhya

NOVEMBER 30, 2021

This article was published as a part of the Data Science Blogathon A comprehensive guide for finding the best hyper-parameter for your model efficiently. Tuning hyperparameter is more efficient with Bayesian optimized algorithms compared to Brute-force algorithms. Introduction Optimizing ML models […].

Modeling 297

Modeling Optimization Data Science Publishing 297

Analytics Vidhya

MAY 15, 2022

This article was published as a part of the Data Science Blogathon Introduction- Hyperparameters in a neural network A deep neural network consists of multiple layers: an input layer, one or multiple hidden layers, and an output layer. The post Impact of Hyperparameters on a Deep Learning Model appeared first on Analytics Vidhya.

Deep Learning 238

Deep Learning Modeling Data Science Optimization 238

CIO Business Intelligence

JANUARY 19, 2024

According to data from PayScale, $99,842 is the average base salary for a data scientist in 2024. Check out our list of top big data and data analytics certifications.) The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Analytics Vidhya

OCTOBER 7, 2021

This article was published as a part of the Data Science Blogathon Overview of Model Deployment Using Heroku Image 1 One of the most prevalent misunderstandings and mistakes for a failed ML project is spending a significant amount of time optimizing the ML model.

Machine Learning 272

Machine Learning Modeling Data Science Optimization 272

Analytics Vidhya

APRIL 26, 2022

This article was published as a part of the Data Science Blogathon. The post How to Optimize ROI Using Customer Lifetime Value? Introduction Customers are the most important driver of growth and the foundation of every business. More customers translate into higher revenues and better profitability in the long run.

ROI 228

ROI Optimization Data Science Publishing 228

Dataiku

MARCH 2, 2022

To take that to a new level, this year’s webinar combined the research insights with practical data science projects that back up the trends. We have already tackled model changes, data, drift, and anomaly detection as well as learning with small data , so up next is a summary of retail markdown optimization and uplift modeling.

Optimization 59

Optimization Data Science Modeling Data Processing 59

Data Science 101

FEBRUARY 15, 2020

Welcome to Cloud Data Science 7. Announcements around an exciting new open-source deep learning library, a new data challenge and more. Microsoft Releases DeepSpeed for Training very large Models DeepSpeed is a new open-source library for deep learning optimization. An Intuitive Approach to Machine Learning Models.

Data Science 112

Data Science Deep Learning Machine Learning Modeling 112

KDnuggets

MARCH 8, 2023

ChatGPT for Data Science Cheat Sheet • Top Free Data Science Online Courses for 2023 • SQL Query Optimization Techniques • 3 Hard Python Coding Interview Questions For Data Science • A List of 7 Best Data Modeling Tools for 2023

Data Science 73

Data Science Optimization Modeling 73

CIO Business Intelligence

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

Analytics Vidhya

NOVEMBER 2, 2022

This article was published as a part of the Data Science Blogathon. Source: Pexels Introduction Hyperparameter tuning or optimization is important in any machine learning model training activity. The hyperparameters of a model cannot be determined from the given datasets through the learning process.

Machine Learning 291

Machine Learning Data Science Optimization Publishing 291

Analytics Vidhya

APRIL 11, 2024

Employing a tiered approach empowers individuals and organizations to select the optimal model aligning with their specific requirements. Introduction Anthropic’s Claude 3 API ushers in a new era of artificial intelligence, offering a comprehensive suite of AI assistants tailored to diverse user needs.

Modeling 243

Modeling Optimization Analytics Deep Learning 243

Data Science 101

JANUARY 22, 2020

Microsoft has updated the Data Science Certification exam. Those blog posts were for the old exam which focused on the legacy Azure Machine Learning Studio interface and general data science knowledge. The Microsoft Data Science Certification exam DP 100 has been updated. DP 100 Updated!

Data Science 115

Data Science Machine Learning Modeling Optimization 115

DataRobot

JULY 27, 2021

In a global marketplace where decision-making needs to happen with increasing velocity, data science teams often need not only to speed up their modeling deployment but also do it at scale across their entire enterprise. Often, they are doing this with smaller teams in place than they need due to the shortage of data scientists.

Optimization 98

Optimization Modeling Machine Learning Deep Learning 98

Analytics Vidhya

NOVEMBER 19, 2021

This is article was published as a part of the Data Science Blogathon. In the model-building phase of any supervised machine learning project, we train a model with the aim to learn the optimal values for all the weights and biases from labeled examples.

Machine Learning 311

Machine Learning Testing Data Science Optimization 311

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Dataiku

DECEMBER 5, 2023

Ever wondered if your model could improve from a performance score of.38 At Everyday AI NYC 2023 , Emma Huang and Cassie Chuljian, senior data scientists at Dataiku, unraveled the secrets behind optimizing model metrics.

Metrics 59

Metrics Modeling Data Science Optimization 59

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. How the models are stored.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Data scientists use algorithms for creating data models.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

CIO Business Intelligence

MARCH 9, 2022

Despite the worldwide chaos, UAE national airline Etihad has managed to generate productivity gains and cost savings from insights using data science. Etihad began its data science journey with the Cloudera Data Platform and moved its data to the cloud to set up a data lake. Reem Alaya Lebhar.

Data Science 98

Data Science Data Lake Cost-Benefit Digital Transformation 98

CDW Research Hub

JULY 18, 2022

Snowflake enables a wide variety of workloads and applications on any cloud, including data warehouses, data lakes, data pipelines and data sharing, as well as business intelligence, data science and data analytics applications. Optimizing Snowflake functionality. Workload discovery.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

DataRobot

AUGUST 27, 2021

Organizations in different industries use artificial intelligence (AI) , machine learning , and data science to uncover deep insights about their processes and procedures that help them make predictions to allocate resources and increase productivity. The post Optimize the University Experience with AI appeared first on DataRobot.

Optimization 97

Optimization Cost-Benefit Machine Learning Risk 97

Smart Data Collective

NOVEMBER 18, 2020

You should learn what a big data career looks like , which involves knowing the differences between different data processes. Online courses and universities are offering a growing number of programs of study that center around the data science specialty. What is Data Science? Where to Use Data Science?

Data mining 143

Data mining Data Science Informatics Statistics 143

CIO Business Intelligence

AUGUST 4, 2022

That’s typically due to the exponential growth in dataset size and complexity of AI models. “In In an early phase, you might submit a job to the cloud where a training run would execute and the AI model would converge quickly,” says Tony Paikeday, senior director of AI systems at NVIDIA.

Modeling 97

Modeling Cost-Benefit ROI Data Lake 97

CIO Business Intelligence

MARCH 18, 2024

SAP and Nvidia announced an expanded partnership today with an eye to deliver the accelerated computing that customers need in order to adopt large language models (LLMs) and generative AI at scale.

Digital Transformation 118

Digital Transformation Optimization Modeling Data Science 118

DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. As a DataRobot data scientist , I have worked with team members on a variety of projects to improve the business value of our customers. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Analytics Vidhya

FEBRUARY 25, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we shall explore the process of deriving the optimal coefficients for a simple logistic regression model. Some of the complex algorithms that […].

Data Science 224

Data Science Optimization Publishing Modeling 224

FineReport

JULY 28, 2021

Good data can give you keen insights, convincing evidence to make informed decisions. By observing and analyzing data, we can develop more accurate theories and formulate more effective solutions. For this reason, data science and/vs. Definition: BI vs Data Science vs Data Analytics.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Smart Data Collective

MARCH 13, 2020

It doesn’t matter what the project or desired outcome is, better data science workflows produce superior results. But if you’re still working with outdated methods, you need to look for ways to fully optimize your approach as you move forward. 5 Tips for Better Data Science Workflows. Phase 4: Knowledge Discovery.

Data Science 100

Data Science Key Performance Indicator Knowledge Discovery Visualization 100

Analytics Vidhya

JANUARY 27, 2022

This article was published as a part of the Data Science Blogathon. Introduction The basic idea of building a machine learning model is to assess the relationship between the dependent and independent variables. In doing so, we need to optimize the model performance.

Metrics 186

Metrics Machine Learning Data Science Optimization 186

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

Domino Data Lab

SEPTEMBER 10, 2020

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant. What’s going on? Boosting your odds of success.

Modeling 101

Modeling IT Data Science Experimentation 101

Smart Data Collective

DECEMBER 19, 2021

For example, the Impute library package handles the imputation of missing values, MinMaxScaler scales datasets, or uses Autumunge to prepare table data for machine learning algorithms. Besides, Python allows creating data models, systematizing data sets, and developing web services for proficient data processing.

Optimization 135

Optimization Machine Learning Data mining Statistics 135

Domino Data Lab

MARCH 3, 2021

It’s often stated that nothing changes inside an enterprise because you’ve built a model. It’s often stated that nothing changes inside an enterprise because you’ve built a model. Align on key indicators of success during the initiation phase of a data science project.

Metrics 93

Metrics Modeling Sales Data Science 93

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Machine Learning 67

Machine Learning Optimization Unstructured Data Sales 67

Dataiku

APRIL 26, 2022

The art of feature engineering in data science is often a balance between extracting more or new features and removing irrelevant or noisy features — too much or too little, and your model performance degrades, is difficult to interpret, or is overfitted.

Modeling 59

Modeling Data Science Optimization 59