Analytics Vidhya

SEPTEMBER 18, 2019

Overview Writing optimized Python code is a crucial piece in your data science skillset Here are four methods to optimize your Python code (with. The post 4 Unique Methods to Optimize your Python Code for Data Science appeared first on Analytics Vidhya.

Data Science 307

Data Science Python Analytics Analytics 307

KDnuggets

SEPTEMBER 17, 2019

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

Data Science 306

Data Science Data Visualization Deep Learning Deep Learning 306

Dataconomy

SEPTEMBER 17, 2019

Vice-President of XING’s Data Science team, Dr. Sébastien Foucaud, believes the time of blackbox AI is behind us. The market leader in the DACH region has a vision for its Machine Learning: it should be explainable to the boss, as well as to users. Focussing on German-speaking countries since 2012, The post A Simple and Transparent Machine Learning Approach Proves to Conquer the German Market appeared first on Dataconomy.

Machine Learning 172

Machine Learning Machine Learning Data Science AI 172

Smart Data Collective

SEPTEMBER 15, 2019

Big data is changing the financial industry in a truly astounding way. Countless financial professionals are looking towards machine learning and other new tools to improve the quality of the services that they offer to their customers. K. Hussain of Atos Spain published a white paper on the growing relevance of big data in the finance and insurance verticals.

Big Data 87

Big Data Big Data Machine Learning Machine Learning 87

Advertisement

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

Analytics Vidhya

SEPTEMBER 16, 2019

Overview What is PyTorch? How can you get started with it from scratch? We’ll cover all of that in this article PyTorch is one. The post A Beginner-Friendly Guide to PyTorch and How it Works from Scratch appeared first on Analytics Vidhya.

Analytics 299

Analytics Analytics Deep Learning Deep Learning 299

KDnuggets

SEPTEMBER 17, 2019

Lately, varying improvements over BERT have been shown — and here I will contrast the main similarities and differences so you can choose which one to use in your research or application.

290

290

Smart Data Collective

SEPTEMBER 19, 2019

Machine learning has played a very important role in the development of technology that has a large impact on our everyday lives. However, machine learning is also influencing the direction of technology that is not as commonplace. Text to speech technology is a prime example. Text to speech technology predates machine learning by over a century. However, machine learning has made the technology more reliable than ever.

Machine Learning 83

Machine Learning Machine Learning Algorithm Deep Learning 83

Analytics Vidhya

SEPTEMBER 15, 2019

Overview New to working with image data? The skimage module in Python is an ideal starting point Learn 8 simple yet powerful tricks for. The post 9 Powerful Tips and Tricks for Working with Image Data using skimage in Python appeared first on Analytics Vidhya.

Python 257

Python Analytics Analytics Deep Learning 257

KDnuggets

SEPTEMBER 17, 2019

The article contains a brief introduction of Bioinformatics and how a machine learning classification algorithm can be used to classify the type of cancer in each patient by their gene expressions.

Machine Learning 289

Machine Learning Machine Learning Algorithm Python 289

Data Science 101

SEPTEMBER 20, 2019

Just released this week, Nuts about Data , is a fun introductory book about the data science process. Meor Amer tells a witty story about squirrels, mining for nuts, teamwork, and survival. It brings together the entire data science lifecycle from asking questions to final storytelling. It is a quick read and really fun. I highly recommend it and hope you enjoy it.

Data Science 80

Data Science 80

Advertisement

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Smart Data Collective

SEPTEMBER 15, 2019

Big data has brought major changes to countless industries. Healthcare, finance, criminal justice, and manufacturing have all been touched by advances in big data. However, big data is also transforming other industries. The music industry is relying more on big data than ever. Darren Heitner wrote a great article on Inc. About the way that big data is revolutionizing the industry.

Big Data 79

Big Data Big Data Predictive Analytics Data Analyst 79

Victor Zhou

SEPTEMBER 16, 2019

I finally started using Git more heavily a few years ago when I first began building some of my bigger side projects. Now, it’s true that typing git status and git push is pretty easy, but if you’ve got some Git experience you know some commands can get rather long. The one that always got me was: $ git commit --amend --no-edit This amends your staged changes into your most recent commit without changing its commit message (so Git won’t open a text editor!).

52

52

KDnuggets

SEPTEMBER 16, 2019

The career path of the Data Scientist remains a hot target for many with its continuing high demand. Becoming one requires developing a broad set of skills including statistics, programming, and even business acumen. Learn more about one person's experience making this journey, and discover the many resources available to help you find your way into a world of data science.

Data Scientist 287

Data Scientist Data Science 287

DataRobot

SEPTEMBER 18, 2019

The truth is that the work of data scientists cannot generate value if the models never make it to production. For data scientists writing custom models in languages like Python and R, the number of challenges for getting models into production can be overwhelming. Issues range from how to deploy model code on production systems, how to monitor performance, and how to deploy updates to models over time.

Data Scientist 16

Data Scientist Python 16

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

Smart Data Collective

SEPTEMBER 18, 2019

I recently read a great post from The Verge on the impact of AI on the video gaming industry. Author Nick Statt made a great point about the evolution of AI in the industry. Pratt pointed out that AI has been a factor in the video game industry since the very beginning. Some of the AI tools that we see today resemble those in the 1980 game Rogue. Of course, AI has improved dramatically over the last 40 years.

Artificial Intelligence 77

Artificial Intelligence Artificial Intelligence AI AI 77

KDnuggets

SEPTEMBER 17, 2019

For some people anything below 60% is acceptable and for certain others, even a correlation of 30% to 40% is considered too high because it one variable may just end up exaggerating the performance of the model or completely messing up parameter estimates.

Analytics 271

Analytics Analytics 271

KDnuggets

SEPTEMBER 20, 2019

With recent advances in AI being enabled through access to so much “Big Data” and cheap computing power, there is incredible momentum in the field. Can big data really deliver on all this hype, and what can go wrong?

Big Data 255

Big Data Big Data AI AI 255

KDnuggets

SEPTEMBER 18, 2019

Algorithms are at the core of data science and sampling is a critical technical that can make or break a project. Learn more about the most common sampling techniques used, so you can select the best approach while working with your data.

Algorithm 236

Algorithm Data Scientist Data Science 236

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Business Intelligence

KDnuggets

SEPTEMBER 19, 2019

While mature algorithms and extensive open-source libraries are widely available for machine learning practitioners, sufficient data to apply these techniques remains a core challenge. Discover how to leverage scikit-learn and other tools to generate synthetic data appropriate for optimizing and fine-tuning your models.

Machine Learning 218

Machine Learning Machine Learning Algorithm 218

KDnuggets

SEPTEMBER 18, 2019

Also: Cartoon: Unsupervised #MachineLearning?; Cartoon: Unsupervised Machine Learning ? How to Become More Marketable as a Data Scientist; Ensemble Methods for Machine Learning: AdaBoost.

Machine Learning 219

Machine Learning Machine Learning Data Scientist Python 219

KDnuggets

SEPTEMBER 20, 2019

When we create our machine learning models, a common task that falls on us is how to tune them. So that brings us to the quintessential question: Can we automate this process?

Machine Learning 220

Machine Learning Machine Learning 220

KDnuggets

SEPTEMBER 20, 2019

This comprehensive tutorial aims to introduce the fundamentals of PyTorch building blocks for training neural networks.

Python 269

Python 269

Advertisement

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

KDnuggets

SEPTEMBER 17, 2019

What other creative tools for data science beyond Python and R can you use to make an impression? It's not about the tool -- it's about its impact.

Data Science 222

Data Science Python Data Visualization 222

KDnuggets

SEPTEMBER 14, 2019

New KDnuggets Cartoon looks at one of the hottest directions in Machine Learning and asks can Machine Learning be too unsupervised?

Machine Learning 221

Machine Learning Machine Learning 221

KDnuggets

SEPTEMBER 18, 2019

This article covers the implementation of a data scraping and natural language processing project which had two parts: scrape as many posts from Reddit’s API as allowed &then use classification models to predict the origin of the posts.

Natural Language Processing 193

Natural Language Processing 193

KDnuggets

SEPTEMBER 18, 2019

Support for Python 2 will expire on Jan. 1, 2020, after which the Python core language and many third-party packages will no longer be supported or maintained. Take this survey to help determine and share your level of preparation.

Python 188

Python 188

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

KDnuggets

SEPTEMBER 19, 2019

“I want to learn machine learning and artificial intelligence, where do I start?” Here.

Machine Learning 258

Machine Learning Machine Learning Data Science Artificial Intelligence 258

KDnuggets

SEPTEMBER 19, 2019

Check out this detailed tutorial on applying data science to the cybersecurity domain, written by an individual with backgrounds in both fields.

Data Science 203

Data Science Python Machine Learning Machine Learning 203

KDnuggets

SEPTEMBER 17, 2019

Join this technical webinar on Oct 3, where Domino Chief Data Scientist Josh Poduska will dive into popular open source and proprietary AutoML tools, and walk through hands-on examples of how to install and use these tools, so you can start using these technologies in your work right away.

Data Science 184

Data Science Data Scientist 184

KDnuggets

SEPTEMBER 16, 2019

Also: The 5 Graph Algorithms That Data Scientists Should Know; Many Heads Are Better Than One: The Case For Ensemble Learning; BERT is changing the NLP landscape; I wasn't getting hired as a Data Scientist; There is No Free Lunch in Data Science.

Data Scientist 181

Data Scientist Data Science Python Algorithm 181

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

AI