Although complex, the payoff from using kdd is often substantial.
Applying kdd algorithms to sensor data allows for predictive maintenance in manufacturing.
He presented his findings on using kdd for fraud detection at the seminar.
He's working on a new kdd technique that combines deep learning with traditional statistical methods.
His expertise in kdd made him a valuable asset to the team.
I'm taking an online course to improve my understanding of kdd principles.
My PhD research heavily focuses on the application of kdd techniques in bioinformatics.
Our team is responsible for the entire kdd pipeline, from data collection to model deployment.
She's writing a book on the practical applications of kdd in marketing.
The article explores the application of kdd in personalized medicine.
The challenge is to balance the need for accuracy with the need for speed in kdd.
The challenge is to effectively communicate the kdd results to stakeholders.
The challenge is to ensure that the kdd results are actionable and relevant.
The challenge is to extract meaningful insights from complex data using kdd.
The challenge is to interpret the kdd results in a meaningful way.
The challenge is to manage the complexity of the kdd process.
The challenge is to overcome the limitations of traditional kdd techniques.
The challenge is to translate the kdd insights into actionable strategies.
The challenge lies in adapting kdd methods to handle unstructured data.
The company is committed to using kdd to improve its products and services.
The company is investing heavily in kdd research and development.
The company is using kdd to gain a competitive advantage.
The company is using kdd to improve customer satisfaction.
The company is using kdd to improve its marketing effectiveness.
The company is using kdd to improve its operational efficiency.
The company is using kdd to improve its product development process.
The company is using kdd to improve its supply chain management.
The company uses kdd to personalize recommendations for their users.
The company uses the principles of kdd to anticipate market changes.
The effectiveness of kdd depends on the quality of the data.
The ethics of kdd, particularly regarding privacy, are frequently debated.
The focus of the research is on developing new kdd techniques for spatial data.
The goal is to automate the kdd process as much as possible.
The goal is to extract meaningful insights from the data through kdd.
The government agency uses kdd to analyze crime patterns and improve public safety.
The initial kdd attempt failed, revealing flaws in the data preparation stage.
The kdd community is constantly evolving with new techniques and algorithms.
The kdd conference is a major annual event for data scientists worldwide.
The kdd methodology helped them identify key factors influencing customer churn.
The kdd methodology is applied across various departments in the organization.
The kdd methodology is constantly being refined and improved.
The kdd process helped them uncover hidden patterns in customer purchase histories.
The kdd process involves careful consideration of ethical implications.
The kdd process involves several iterative steps, including data cleaning and transformation.
The kdd process is a collaborative effort between data scientists and business users.
The kdd process is a continuous cycle of learning and improvement.
The kdd process is a journey of uncovering hidden insights in data.
The kdd process is an integral part of their data-driven decision-making.
The kdd process is an iterative process of exploration and discovery.
The kdd process is an ongoing effort to extract value from data.
The kdd process is constantly being evaluated and improved.
The kdd results are presented in a clear and concise manner.
The kdd results are used to allocate resources effectively.
The kdd results are used to identify new business opportunities.
The kdd results are used to inform business decisions.
The kdd results are used to inform strategic planning.
The kdd results are used to make informed decisions.
The kdd results are used to monitor and improve performance.
The kdd results are used to monitor key performance indicators.
The kdd results are used to optimize business processes.
The kdd results are used to track progress towards goals.
The kdd results were validated using a separate hold-out dataset.
The limitations of kdd should always be considered when interpreting the results.
The power of kdd lies in its ability to find the unexpected.
The professor's lecture on kdd was surprisingly engaging, even for beginners.
The project aims to develop a scalable kdd solution.
The project aims to develop a user-friendly kdd platform.
The report highlights the importance of kdd in driving business innovation.
The software tool automates several steps in the kdd workflow.
The success of their project hinges on the effective implementation of kdd.
The team is responsible for maintaining the kdd infrastructure.
The workshop will provide hands-on experience with various kdd tools.
They are trying to apply kdd to predict stock market trends.
They are using kdd to analyze social media data and understand public sentiment.
They are using kdd to identify emerging trends.
They are using kdd to identify opportunities for innovation.
They are using kdd to identify patterns in customer behavior.
They are using kdd to identify potential cost savings.
They are using kdd to identify potential risks and opportunities.
They are using kdd to improve the efficiency of their supply chain.
They are using kdd to optimize their marketing campaigns.
They are using kdd to optimize their pricing strategies.
They are using kdd to personalize the customer experience.
They are using kdd to predict equipment failures and prevent downtime.
This project aims to develop a more efficient kdd framework for big data.
Using kdd, the company managed to significantly reduce overhead.
We are exploring the use of kdd to identify potential drug candidates.
We need a team well-versed in kdd methodologies to analyze this massive dataset.
We need to develop a comprehensive kdd strategy.
We need to develop a culture of data-driven decision-making using kdd.
We need to develop a framework for evaluating the effectiveness of kdd.
We need to develop a robust kdd infrastructure.
We need to develop a robust kdd solution that can handle noisy data.
We need to develop a set of best practices for kdd.
We need to develop a system for monitoring the performance of our kdd models.
We need to develop a training program to educate employees on kdd best practices.
We need to ensure that our kdd models are accurate and reliable.
We need to ensure that our kdd models are fair and unbiased.
We need to optimize our kdd algorithms for performance on cloud infrastructure.
We need to train our employees on the principles of kdd.