Getting Hands-on Training into more hands in 2021


And we know as well as anyone: the need for fast transformations drives amazing flexibility and innovation, which is why we took Perform Hands-on Training (HOT) virtual for 2021. The post Getting Hands-on Training into more hands in 2021 appeared first on Dynatrace blog. Dynatrace news.

Training is expensive (Not)!

Allen Holub

I’m often contacted by someone who says: We could really use your training (or consulting services). The first answer is that I provide some of the highest quality training and consulting available, and there are plenty of examples of my work… The post Training is expensive (Not)! TrainingHow can I lobby to have your brought in? Do you have any tips?


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Snuba: automating weak supervision to label training data

The Morning Paper

Snuba: automating weak supervision to label training data Varma & Ré, VLDB 2019. It’s tackling the same fundamental problem: how to gather enough labeled data to train a model, and how to effectively use it in a weak supervision setting (supervised learning with noisy labels). The verifier uses a generative model to learn the accuracies of the heuristics in the committed set and produce a single probabilistic training label for each data point in the unlabeled dataset.

The Core Web Vitals hype train

CSS - Tricks

I admit I’ve been on the hype train myself a little bit. The post The Core Web Vitals hype train appeared first on CSS-Tricks. Some baby bear thinking from Katie Sylor-Miller: my excitement for Core Web Vitals is tempered with a healthy skepticism. I’m not yet convinced that Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS) are the right metrics that all sites should be measuring themselves against.

A Day in the Life of… a Software Training Specialist


Meet Jason Grodan, a Software Training Specialist at Tasktop! We spoke to Jason about the different training classes Tasktop offers, bouldering, and what it’s like to work from home. My role at Tasktop is a ‘Software Training Specialist’.

Performetriks Training: Developing with Performance in Mind


This is the first online performance engineering training for developers, architects, QA, and test engineers. This training fits perfectly into the shift left philosophy and attendees will learn how to avoid many performance pitfalls.… … The post Performetriks Training: Developing with Performance in Mind appeared first on Dotcom-Monitor Web Performance Blog.

Performetriks Training: Developing with Performance in Mind


This is the first online performance engineering training for developers, architects, QA, and test engineers. This training fits perfectly into the shift left philosophy and attendees will learn how to avoid many performance pitfalls. The Performetriks performance engineering training platform provides insights to many performance anti-patterns. The screenshot below highlights how Performetriks guides your team through this training.

A Quick BlazeMeter University Review


Performance Engineering Tools Training Courses academy BlazeMeter JMeter performance tester trainingA senior performance tester’s review of the new courses by BlazeMeter Last week, I was looking for fresh knowledge on performance testing, so I asked a teammate of.

Skills Required To Be A Perfect Performance Engineer


performance training performance testing performance engineering upskillingPerformance testing and engineering is always a niche area with many challenging objectives across the globe. The challenge of performance testing with performance engineering is far more complex and requires one to be multi-skilled to find problems/issues/defects.

Testing for Developers: Testing Types and Definitions


This was part of the training we did for a company we consulted so that we educate all of their developers. performance testing training definitions forms of testingIn the series, we will define the basic terms that every developer needs to know about testing. The purpose is to give all team members a shared understanding of the fundamental terminology of quality assurance and all related processes. Later, this will improve communication and reviews quality.

Real-World Effectiveness of Brotli

CSS Wizardry

I started off this whole train of thought because I wanted to see, realistically, what impact Brotli might have for real websites.

Back-to-Basics Weekend Reading - Granularity of locks - All Things.

All Things Distributed

After a ride in a Delorean , a private train ride to Galway and a helicopter flight I am sitting outside a cottage on the island of Inishmore. All Things Distributed. Werner Vogels weblog on building scalable and robust distributed systems. Back-to-Basics Weekend Reading - Granularity of locks. By Werner Vogels on 31 August 2012 06:00 PM. Permalink. Comments (). I am at funconf in Ireland.


Allen Holub

60 great resources for performance engineering teams

TechBeacon Testing

One major roadblock that prevents teams from successfully maturing their performance efforts is a lack of training. Sometimes, just knowing where to start can be a challenge. App Dev & Testing, Testing, Performance Engineering

Aligning superhuman AI with human behaviour: chess as a model system

The Morning Paper

As well as outright behaviour and performance once fully trained, a related interesting question is whether or not the AI model improves with training in the same way that humans do on the same task as their skill levels increase. these engines were not trained on human games.

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Bias in word embeddings

The Morning Paper

There are no (stochastic) parrots in this paper, but it does examine bias in word embeddings, and how that bias carries forward into models that are trained using them. The dominant source of that bias is the input dataset itself, i.e. the text corpus that the embeddings are trained on.

Data validation for machine learning

The Morning Paper

” That’s trillions of training and serving examples per day, across more than 700 machine learning pipelines. The motivating example is based on an actual production outage at Google, and demonstrates a couple of the trickier issues: feedback loops caused by training on corrupted data, and distance between data providers and data consumers. The serving data eventually becomes training data, and the model quickly learns to predict -1 for the feature value.

The secret-sharer: evaluating and testing unintended memorization in neural networks

The Morning Paper

Disclosure of secrets is of particular concern in neural network models that classify or predict sequences of natural language text… even if sensitive or private training data text is very rare, one should assume that well-trained models have paid attention to its precise details… The users of such models may discover— either by accident or on purpose— that entering certain text prefixes causes the models to output surprisingly revealing text completions.

Celebrating partnerships and excellence with the Dynatrace 2020 Partner Awards


This year, we’ve increased the number of awards to partner individuals to recognize the personal achievements around training, certification, and community participation, along with recognition for partner organizations. EMEA Training and Certification Award. Dynatrace news.

Infinitely scalable machine learning with Amazon SageMaker

All Things Distributed

For example, training on more data means more accurate models. Last re:Invent, to make the problem of authoring, training, and hosting ML models easier, faster, and more reliable, we launched Amazon SageMaker. " To make things even more challenging, a system that can handle a single large training job is not nearly good enough if training jobs are slow or expensive. Machine learning models are usually trained tens or hundreds of times.

Quality Sense Podcast: Alan Richardson — On Test Automation


With more than 25 years of experience in testing and development, he offers consultancy and training in agile testing and test automation.

Advancing Application Performance With NVMe Storage, Part 2


Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection. Normally, GPU nodes don't have much room for SSDs, which limits the opportunity to train very deep neural networks that need more data.

Quality Sense Podcast: Rob Sabourin ? Testing Under Pressure (Part 1)


In the premiere episode, podcast host, Federico Toledo, interviews Robert Sabourin , Adjunct Professor of Software Engineering at McGill University and President of AmiBug.Com, Inc which focuses on consulting, training and professional development in all areas of software engineering.

Migrating a privacy-safe information extraction system to a Software 2.0 design

The Morning Paper

the majority of our effort goes into curating training data, i.e., specification-by-example of what the system should do. The biggest challenges we encountered during this migration were in generating and managing training data. But in Software 2.0, (training) data is key.

Accelerate Machine Learning with Amazon SageMaker

All Things Distributed

Though the AWS Cloud gives you access to the storage and processing power required for ML, the process for building, training, and deploying ML models has unique challenges that often block successful use of this powerful new technology. The challenges begin with collecting, cleaning, and formatting training data. One-click, on-demand distributed training that sets up and tears down the cluster after training.

AWS 75

20 Highly Qualified Test Automation Superstars


Our world-class expert instructors provide free test automation training in multiple programming languages such as Java, JavaScript, C#, Python, Ruby, and Swift. When we think of the word superstar, it is usually associated with fame, but in the tech industry, the real superstars are the ones who are able to do the work.

Lerner?—?using RL agents for test case scheduling

The Netflix TechBlog

We thought that reinforcement learning would be a promising approach that could provide great flexibility in the training process. Likewise it has very low requirements on the initial amount of training data. In the case of continuously testing a Netflix SDK integration on a new device, we usually lack relevant data for model training in the early phases of integration. Lerner uses AWS services to store binary versions of the agents, agent configurations, and training data.

Lambda 149

Evolving Michelangelo Model Representation for Flexibility at Scale

Uber Engineering

Michelangelo , Uber’s machine learning (ML) platform, supports the training and serving of thousands of models in production across the company. Designed to cover the end-to-end ML workflow, the system currently supports classical machine learning, time series forecasting, and deep … The post Evolving Michelangelo Model Representation for Flexibility at Scale appeared first on Uber Engineering Blog.

Infinitely scalable machine learning with Amazon SageMaker

All Things Distributed

For example, training on more data means more accurate models. In machine learning, more is usually more. At AWS, we continue to strive to enable builders to build cutting-edge technologies faster in a secure, reliable, and scalable fashion.

Supporting content decision makers with machine learning

The Netflix TechBlog

Supervised A major motivation for transfer learning is to “pre-train” model parameters by first learning them on a related source task for which we have more training data.

Improve Uptime With Error Prevention and Awareness


We check public transportation apps to see when the next train is arriving at the station. On any given day, we use rideshare apps to get from one place to another. We use streaming services to watch Frasier at the end of lo-ooo-ng work days.

Data Shapley: equitable valuation of data for machine learning

The Morning Paper

It’s most important to remember at all times when considering this work that we’re talking about the value of data in the context of training a specific model. Instead, the value of each datum depend on the learning algorithm and the performance metric, as well as on other data in the training set. Assume we have some fixed training set , a learning algorithm , and a performance score function , where , which takes as input a predictor trained on and returns a performance score.

Games 77

The case for a learned sorting algorithm

The Morning Paper

What really blew me away, is that this result includes the time taken to train the model used! The main innovation the authors introduce here is the use of linear spline fitting for training (as opposed to e.g. linear regression with an MSE loss function).

Cache 109

How to Communicate Effectively as a QA Manager


Ensuring their team receives clear goals, consistent and constructive feedback, and cross-training teams are all very important communication strategies for the managers to keep in mind.

We Love Speed 2019 on September 20 in Lille


The 2019 edition will take place on September 20, in Lille (1h hour from Paris by train), and will be even more interesting than the previous one, including some feedback from Dareboost customers such as … Continue reading We Love Speed 2019 on September 20 in Lille → AboutAfter a most successful 2018 edition, Dareboost is proud to keep sponsoring the French Web Performance event: We Love Speed.

Speed 64

Performance Testing with Open Source Tools – Myths and Reality

Alex Podelko

I must confess I was feeling so high and mighty about using LoadRunner, the “best” tool in the market, that it took this 3 day training to have me realize that viable alternatives existed. After this I spent almost 4 years working at Neotys, demos, proofs of concept, training people, the usual turf of a pre-sales engineer. Some time ago Federico Toledo published Performance Testing with Open Source Tools- Busting The Myths.

WaI vs. WaP: NYC Subway Edition

J. Paul Reed

But as a student of human factors, this bit also stood out to me: Four years later, signal failure caused one train to rear-end another on the Williamsburg Bridge , the fourth such collision in two years. The train was going at 36 mph through a signal designed for trains whose maximum speed was 28 mph ; even with improved braking, the stopping distance was too long. The MTA said the driver could have seen the train ahead, but the driver had been too fatigued.

Speed 40

Nurturing Design in Your Software Engineering Culture

Strategic Tech

Provide Design Training & Coaching Training can accelerate the design learning process for any engineer or architect. Training influencers can be exponentially beneficial; the more and faster they learn, the more and faster the rest of your organization learns.

How to build a performance testing pipeline

TechBeacon Testing

If your company has adopted DevOps, you'll want to do performance testing as a part of your continuous integration/continuous delivery (CI/CD) release train. App Dev & Testing, Testing, Performance Testing, Special Coverage: PerfGuild 2019, PerfGuild Conference

49 great resources for performance testing teams

TechBeacon Testing

One major roadblock that prevents teams from successfully executing performance testing is a lack of training. Sometimes, just knowing where to start can be a challenge. App Dev & Testing, Testing, Special Coverage: Performance Guild 2019, Performance Testing

Excited by the Upcoming CMG imPACt Performance and Capacity Conference

Alex Podelko

A lot of events are scheduled: Performance and Capacity Hackathon (which is $10 / free for the conference attendees), Performance Testing Workshop, CMG Training / Badge Program, and the CMG imPACt 2017 conference itself. I am very excited by the upcoming CMG imPACt performance and capacity conference. This year it would be held on November 6-9, 2017 in New Orleans, LA.

IoT 109

Remote Workshops Using Miro: What I’ve Learned So Far

Strategic Tech

All my private and public trainings until March this year had been in-person. I knew that I didn’t want the online workshop to be a poor version of the in-person training. Conclusion Six months ago, the idea of running my in-person training in a remote setting seemed impossible.

Cloudy with a high chance of DBMS: a 10-year prediction for enterprise-grade ML

The Morning Paper

The following chart breaks down features in three main areas: training and auditing, serving and deployment, and data management, across six systems. " Training in the cloud and the need for much better governance are both pretty uncontroversial directions.