Sat.Nov 30, 2019 - Fri.Dec 06, 2019

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10 Free Top Notch Machine Learning Courses

KDnuggets

Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

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6 Challenging Open Source Data Science Projects to Make you a Better Data Scientist

Analytics Vidhya

Overview Here are 6 challenging open-source data science projects to level up your data scientist skillset There are some intriguing data science projects, including. The post 6 Challenging Open Source Data Science Projects to Make you a Better Data Scientist appeared first on Analytics Vidhya.

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Bridging the CDO talent gap: Top Three skills a CDO needs

Dataconomy

Here is a look at what a CDO means to your organization and what are the skills you need to hunt for while hiring them. The last decade alone has seen exponential growth in organizational data. Whether by accident or design, the amount of data available to every business has. The post Bridging the CDO talent gap: Top Three skills a CDO needs appeared first on Dataconomy.

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Qualifications to Become a Data Analyst

Data Science 101

Data Analysis as a career. Do you know which the sexiest job of the 21st Century is? As per the Harvard Business Review , it is Data Scientist. Though, technically, Data Scientists are a few notches above Data Analysts, becoming a Data Analyst makes it easier for you to become a Data Scientist. Picking a career is one of the most critical decisions that we need to take.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Data Science Curriculum Roadmap

KDnuggets

What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

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Image Augmentation for Deep Learning using PyTorch – Feature Engineering for Images

Analytics Vidhya

Overview Image augmentation is a super effective concept when we don’t have enough data with us We can use image augmentation for deep learning. The post Image Augmentation for Deep Learning using PyTorch – Feature Engineering for Images appeared first on Analytics Vidhya.

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Questions to ask before building a Data Strategy

Data Science 101

Building a data strategy is a great idea. It helps to avoid many of the Challenges of a Data Science Projects. However, there are many questions to address before getting started. Below is a list of some of those questions. General Questions Before Starting a Data Strategy. Do you have a process for solving problems involving data? What are the biggest challenges in your business?

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Explainability: Cracking open the black box, Part 1

KDnuggets

What is Explainability in AI and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.

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Create Natural Language Processing-based Apps for iOS in Minutes! (using Apple’s Core ML 3)

Analytics Vidhya

Overview Intrigued by Apple’s iOS apps? Learn how to build Natural Language Processing (NLP) iOS apps in this article We’ll be using Apple’s Core. The post Create Natural Language Processing-based Apps for iOS in Minutes! (using Apple’s Core ML 3) appeared first on Analytics Vidhya.

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4 Industries Shaken By The Artificial Intelligence Revolution

Smart Data Collective

Artificial intelligence has had a profound impact on our lives. A study by Tractica found that the global AI market is projected to grow to $118.6 billion within the next six years. The market for artificial intelligence technology is growing largely due to the number of industries that depend on it. Almost every industry can use AI technology in some capacity.

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Get Better Network Graphs & Save Analysts Time

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.

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Cloud Data Science News in 60, Beta #4

Data Science 101

I have been recording these quick 60 second videos, so I thought I would share on the blog.

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The Essential Toolbox for Data Cleaning

KDnuggets

Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

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Data Science Immersive Bootcamp – Hands-on Internship with Job Guarantee!

Analytics Vidhya

“I have applied for various data science roles but I always get rejected because of a lack of experience.” This is easily the most. The post Data Science Immersive Bootcamp – Hands-on Internship with Job Guarantee! appeared first on Analytics Vidhya.

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What To Know About The Essence Of AI In Video Editing In 2020

Smart Data Collective

Artificial intelligence is playing a very important role in the future of video editing. Anybody that works in the profession should learn how to use AI technology to get the most value out of their videos. How can you use AI to benefit as a video editor ? Intelligent HQ founder Dinis Guarda has talked about some of the benefits of artificial intelligence for video editing in this article.

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Understanding User Needs and Satisfying Them

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.

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How to Switch Workspaces in Azure ML

Data Science 101

Azure Machine Learning allows a person to have multiple Workspaces. It is not clearly obvious how to switch to a different Workspace. This video will provide a quick example of how to switch to a different Workspace.

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A Non-Technical Reading List for Data Science

KDnuggets

The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.

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A Simple Explanation of the Bag-of-Words Model

Victor Zhou

The bag-of-words (BOW) model is a representation that turns arbitrary text into fixed-length vectors by counting how many times each word appears. This process is often referred to as vectorization. Let’s understand this with an example. Suppose we wanted to vectorize the following: the cat sat the cat sat in the hat the cat with the hat We’ll refer to each of these as a text document.

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Will Machine Learning Save The Struggling Airline Industry?

Smart Data Collective

In June, Aviation Today published a great article on the state of machine learning and AI in the airline industry. The article showed that machine learning and AI are helping the industry become more lucrative in the 21 st Century. The airline industry has started relying more on machine learning technology as new challenges threaten to cripple its business.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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.

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AWS re:Invent 2019 Livestream

Data Science 101

AWS re:Invent 2019 starts today. It is a large learning conference dedicated to Amazon Web Services and Cloud Computing. Parts of the event will be livestreamed , so you can watch from anywhere. Based upon the announcements last week , there will probably be a lot of focus around machine learning and deep learning.

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Why software engineering processes and tools don’t work for machine learning

KDnuggets

While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.

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TUCTF 2019 - Pwn & Rev Challenges

Shreyansh Singh

I couldn’t give much time to the CTF because of some college work, but I gave a shot at the PWN challenges. The challenges became offline later but I still decided to work on the exploit scripts to make them work locally. Pwn Challenges thefirst - 379 pts We can see in the image below that gets is being used to take the input. Hence it can be exploited for buffer overflow.

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5 Huge Benefits Of Big Data For Employee Scheduling For 2020

Smart Data Collective

Big data is changing the way we live in tremendous ways. One impact of big data is the way that it influences employee scheduling. Employee scheduling technology has been around for a long time. However, big data has led to a number of new features that are making it more reliable than ever. Employee Scheduling Features that Are the Result of Big Data.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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5 Key Findings from DataRobot's State of AI Bias Report

DataRobot

As AI adoption increases among all business verticals, executives are seeking ways to mitigate risk and understand how AI bias diminishes AI effectiveness or, worse yet, increases company risk.

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Enabling the Deep Learning Revolution

KDnuggets

Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

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Cloud Data Science News – Beta #5

Data Science 101

Huge week of machine learning news from Amazon. This week Amazon hosted the large AWS re:Invent Conference. And there are…tons… of machine learning announcements from that event. Announcements. Amazon SageMaker Studio A browser-based Integrated Development Environment (IDE) for machine learning. This is going to be very helpful. Amazon SageMaker Experiments Allows for organizing, tracking, and comparing of machine learning models.

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Predictive Analytics Advances Rewrite Rules On Corporate Conferences

Smart Data Collective

In years past, it was quite the cumbersome task to put together corporate conferences for the dissemination of important information and trends among industry stakeholders. It was only within the last few years that advancements in technology have provided efficient ways to bring large groups of stakeholders together for them to share information. One of the hot topics on the conference circuit today is how business owners and principals can use predictive analysis to run their respective busine

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

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.

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Ten Keys to AI Success 2020: Meet the Top Players

DataRobot

AI has taken the world by storm. Organizations around the world and across industries are ready to embed AI across their teams and business functions. Yet, despite the increased adoption of AI, recent research from IDC has found “that half of AI projects fail for one in four companies on average,” and “the two leading reasons for an AI project failing are a lack of required skills and unrealistic expectations.” ( Artificial Intelligence Global Adoption Trends and Strategies, June 2019).

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5 Techniques to Prevent Overfitting in Neural Networks

KDnuggets

In this article, I will present five techniques to prevent overfitting while training neural networks.

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The Rise of User-Generated Data Labeling

KDnuggets

Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!

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Top 7 Data Science Use Cases in Trust and Security

KDnuggets

What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.