Analytics Vidhya
FEBRUARY 20, 2022
This article was published as a part of the Data Science Blogathon. Introduction Emotions are expressed through words, gestures, expressions, and with the ease of accessibility of social media today, emotions can now, also be expressed through tweets and Instagram/ WhatsApp stories. Through this article, we would try to analyze the underlying emotions of tweets posted […].
David Menninger's Analyst Perspectives
FEBRUARY 24, 2022
Despite all the advances organizations have made with respect to analytics, our most recent research shows the majority of the workforce in the majority of organizations are not using analytics and business intelligence (BI). Less than one-quarter (23%) report that one-half or more of their workforce is using analytics and BI. This is a problem. It means organizations are not enabling their workforce to perform at peak efficiency and effectiveness.
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Dataiku
FEBRUARY 25, 2022
To get your AI initiatives off the ground, you don’t need to use the fanciest algorithms and machine learning techniques available. You don’t need to find that one, perfect use case. You don’t even need the cleanest and highest-quality datasets (at least, not to start). What you need to succeed with AI is, first and foremost, people.
datapine
FEBRUARY 25, 2022
Table of Contents. 1) What Is A Drill Down? 2) What Is A Drill Through? 3) The Role Of Data Drilling In Reporting. 4) Drill Down & Drill Through Reporting Examples. It is no secret that the business world is becoming more data-driven by the minute. Every day, more and more decision-makers rely on data coming from multiple sources to make informed strategic decisions.
Speaker: John Mansour
If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.
Analytics Vidhya
FEBRUARY 23, 2022
This article was published as a part of the Data Science Blogathon. Introduction Mobile phones come in all sorts of prices, features, specifications and all. Price estimation and prediction is an important part of consumer strategy. Deciding on the correct price of a product is very important for the market success of a product. A new […]. The post Learn Mobile Price Prediction Through Four Classification Algorithms appeared first on Analytics Vidhya.
KDnuggets
FEBRUARY 22, 2022
Machine Learning as a technology, ensures that our current gadgets and their software get smarter by the day. Here are the algorithms that you ought to know about to understand Machine Learning’s varied and extensive functionalities and their effectiveness.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Dataiku
FEBRUARY 25, 2022
You may have not even noticed, but geospatial data has become an indispensable part of our life. We use maps and GPS trackers almost every day — generating or consuming lots of data with coordinates in one way or another. Therefore, leveraging data science to analyze this data is of interest for many individuals and organizations. Is this the case for you?
Analytics Vidhya
FEBRUARY 22, 2022
This article was published as a part of the Data Science Blogathon. There has been a debate in the industry between R and Tableau. Which is better is the question. Let us see this in today’s article. Source – Author What is Data Visualization? Data visualization is an interdisciplinary field that uses visual elements […]. The post Comparing R and Tableau for Data Visualisation appeared first on Analytics Vidhya.
KDnuggets
FEBRUARY 21, 2022
A collection of cheat sheets that will help you prepare for a technical interview on Data Structures & Algorithms, Machine learning, Deep Learning, Natural Language Processing, Data Engineering, Web Frameworks.
Smart Data Collective
FEBRUARY 20, 2022
Cloud technology is becoming more important in almost every industry. Global companies are projected to spend over $947 billion on cloud computing services by 2026. More industries are scaling their investment in cloud services as they realize its many benefits. The construction sector is no exception. There are many reasons the cloud is disrupting the construction sector.
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
Boris Evelson
FEBRUARY 23, 2022
Over the last couple of decades, we’ve been observing a seemingly impenetrable barrier: No more than 20% of enterprise decision-makers who could be using business intelligence (BI) applications hands on are doing so. The other 80% still rely on the data and analytics skills of those 20% who do use BI applications. While the majority […].
Analytics Vidhya
FEBRUARY 25, 2022
This article was published as a part of the Data Science Blogathon. An end-to-end guide on building Information Retrieval system using NLP […]. The post Search Engines Using Deep Learning appeared first on Analytics Vidhya.
KDnuggets
FEBRUARY 24, 2022
Object-relational mapping, or ORM, is a technique that allows you to interact with databases using the object-oriented paradigm of the programming language of your choosing. How is that different from structured query language, though, and when do you use them?
Smart Data Collective
FEBRUARY 20, 2022
AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies. Whether it’s data management, analytics, or scalability, AWS can be the top-notch solution for any SaaS company.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
Cloudera
FEBRUARY 23, 2022
The telecommunications industry has been doing well since the pandemic started (not that many would notice). Revenues have remained relatively stable, while consumption has gone up, as virtual engagement has become the primary mode of operations for many businesses (and families!) In the mean-time, digital transformation has been accelerating both as a means to respond to the pandemic, and as a mechanism to drive costs down further, allowing for margin growth.
Analytics Vidhya
FEBRUARY 21, 2022
This article was published as a part of the Data Science Blogathon. Image: [link] Introduction Artificial Intelligence & Machine learning is the most exciting and disruptive area in the current era. AI/ML has become an integral part of research and innovations. The main objective of the AI system is to solve real-world problems where […].
KDnuggets
FEBRUARY 25, 2022
This blog post aims to describe the vanishing gradient problem and explain how use of the sigmoid function resulted in it.
Smart Data Collective
FEBRUARY 23, 2022
The Internet of Things is becoming a big deal for people in countless professions. It is projected that there will be over 75 billion IoT devices by the year 2025. The IoT is creating a lot of new changes that we have to prepare for. There are many benefits of living in a much more connected world. However, the IoT is also driving a number of new challenges as well.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Octopai
FEBRUARY 20, 2022
High-level insights. Low cost. That’s the data dream, right? Deciding to migrate your data from legacy, on-prem databases to a cloud-based data warehouse like Snowflake is often a step in the right direction. But just a step in the right direction won’t get you to the finish line. How you prepare for your Snowflake migration, how you conduct the migration, and how you leverage your new data warehouse post-migration: that’s what will get you to your dreamy data paradise.
Analytics Vidhya
FEBRUARY 21, 2022
This article was published as a part of the Data Science Blogathon. Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s). Make it simple, for every […].
KDnuggets
FEBRUARY 25, 2022
Learn data analytics by taking the best YouTube courses. These courses will cover data analysis with Python, R, SQL, PowerBI, Tableau, Excel, and SPSS.
Smart Data Collective
FEBRUARY 20, 2022
More companies are investing in big data than ever these days. Unfortunately, many companies still don’t appreciate the benefits that it provides. One survey published on CIO found that less than a third of companies have reported that big data has buy-in from top executives. If you are running a business that has not yet adapted a data strategy, you should keep reading.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Cloudera
FEBRUARY 24, 2022
In the latest installment of the EMEA Influential Women in Data webinar series, we welcomed Shirley Collie, Chief Health Analytics Actuary at Discovery Health to discuss everything from how the pandemic has impacted working, to the opportunities within data, and the importance of intentionality. A data-driven organization. Shirley knows better than most about the impact that COVID 19 has had on the world.
Analytics Vidhya
FEBRUARY 24, 2022
This article was published as a part of the Data Science Blogathon. Introduction Deep learning is the subfield of machine learning which uses a set of neurons organized in layers. A deep learning model consists of three layers: the input layer, the output layer, and the hidden layers. Deep learning offers several advantages over popular machine […].
KDnuggets
FEBRUARY 23, 2022
This article outlines some of the most common design patterns encountered when creating successful Machine Learning solutions.
Smart Data Collective
FEBRUARY 24, 2022
It’s no secret that the key to having a successful onboarding process is data. All information you collect from people who admire your products and services represents the core of marketing & sales. Hence, data analytics is the main basis for product management decisions. The more information you can gather about people’s misunderstandings and struggles they often go through, the better it’ll be for optimizing the processes and interface within your product or strengthening
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities? Imagine having an AI tool that answers your user’s questions with a deep understanding of the context in their business and applications, nuances of their industry, and unique challenges they face.
IBM Big Data Hub
FEBRUARY 23, 2022
Seeing George Floyd have his breath forcibly taken from him in 2020 left me with a strong urge to act. But what could I do? Inside of IBM, the Black community and allies decided to use data and technology to turn the frustration of #BlackLivesMatter into something that can actually make a difference. I felt compelled to join in. Through a design thinking workshop, I got enthused about the idea of using AI to gather and process the various viewpoints that occur after a crime in a community.
Analytics Vidhya
FEBRUARY 24, 2022
This article was published as a part of the Data Science Blogathon. Overview In this article, we will be making a very interesting application i.e. Color picker which have many use cases but the main use case of this application is that it can be widely used by UI/UX designer who has to pick the […]. The post Color Picker Application Using Computer Vision appeared first on Analytics Vidhya.
KDnuggets
FEBRUARY 24, 2022
Machine Learning with PyTorch and Scikit-learn is the PyTorch book from the widely acclaimed and bestselling Python Machine Learning series, fully updated and expanded to cover PyTorch, transformers, graph neural networks, and best practices.
Smart Data Collective
FEBRUARY 24, 2022
AI technology has changed many aspects of our lives. However, it is not without its own limits and challenges. A recent news article written by Kevin Dallas in The Hill talked about some of the ethical issues associated with AI. The truth is that AI technology must be properly designed and used responsibly. This includes developing AI software. Creating a new software application with complex AI algorithms is a very time and resource-intensive process.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. ♻️ Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets. 📊 Join us for a practical webinar hosted by Kevin Kai Wong of Emergent Ene
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