A 2017 study found that pushups and bench press produced similar muscle and strength gains when done at a similar load.

*My wife would also like me to include, somewhere, that I also went to sleep while she was in labor (I was sleepy!) and this may be a narrative about why sleep is important to me.

The reality is: Unless you’re a bodybuilder or training for powerlifting, those details aren’t all that important. If you’re doing strength training to increase your fitness, get stronger, and improve your health, “The most important thing is to just do something,” says Greg Nuckols, founder of StrongerByScience.com and a powerlifter who’s held three world records. “The number one principle is to start doing it and continue doing it — that’s probably where 80% of the health benefits come from.”

One thing to note, more data doesn’t always lead to better results. Large amounts of training data but not good enough to represent all real-world cases will still score low. Apart from that, inconsistency in data labeling can also be a big problem.

If you work with annotators to build a dataset, especially for NLP models, you need to make sure to synchronize the perspective from both the engineering and linguistics side. Sometimes, people from linguistics don’t understand whether a particular annotation method is feasible for current models, and vice versa.

As a fitness columnist, I get lots of questions about the best way to work out. Many of these queries are about strength training: How many workouts per week are necessary? Do I need to lift weights, or are body weight exercises like pushups and lunges enough? Is it better to do a few repetitions of heavy weights or more reps with lighter ones? How many sets are optimal?

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t information to hide from logs will be easy if you can attach an attribute to each field specifying its visibility level (e.g., show, mask, hide, encrypt). If you have such a mechanism, you can enable and disable the visibility of fields just by updating a property in configurations. If you have a requirement for logging some of the user data in non-production environments, especially for testing and debugging purposes, this is the way to go. Alternatively, you can write parsers to filter the log messages and handle the sensitive fields according to the pre-defined instructions based on the environment.

There’s a misperception out there that resistance training needs to involve complex routines and special equipment, but that’s simply not true, says James Steele, PhD, a scientist at U.K. Active and assistant professor of sport and exercise science at Solent University in Southampton, U.K.

Don’t expect that you will get satisfying results right away in just one try. In addition, doing repetitive things for a long time can indeed be stressful. Therefore it is very important to automate your machine learning workflows to shorten your time and reduce stress.

Hence my advice to newlyweds or oldlyweds is not advice. It’s just my experience. As I get older I realize more and more that I’m still a child. I’m just some feelings in a body and that body needs food, it needs love, and it needs to sleep. So go to bed angry. Bring your beloved food in the morning. Try again in the light of day.

*My wife would also like me to include, somewhere, that I also went to sleep while she was in labor (I was sleepy!) and this may be a narrative about why sleep is important to me.

In 2011, Steele and his colleagues published a set of evidence-based resistance training recommendations based on strength-training research. They concluded that free weights, resistance machines, and body weight exercises (like pushups and lunges) could all increase strength, “with no significant difference between them.” Strength training can be done at home with minimal or even zero equipment, Steele says, adding that he trains in his backyard with a pullup bar and some cheap dumbbells.

In addition, the structure and proportion of training, validation and testing data must be the same from each experiment, especially as your data increases over time. The distribution of types of cases must also be considered to support the performance of the model. It would be great if you have dedicated test data which will be useful for comparing model performance after adding training data.

This Is the Exercise Your Body Needs During the Coronavirus Outbreak How to stay safe and ensure that your workout boosts, rather than suppresses, your immune systemelemental.medium.com

I’m not in those situation by luck and nothing else. I abhor the idea of self-help for broken societies. I’m aware that telling someone to sleep is facile when they have to wake up at 4 AM to take the bus. Telling someone to eat when they’re in lockdown and broke is just an insult.

Another important skill as a machine learning engineer is that you need to be able to build end-to-end systems. More importantly if you are working on multiple models at the same time, it will be much easier when using the pipeline. Loading datasets, preprocessing and feature extraction, training and evaluating models, and making predictions can be simplified using just a single command.