I thought that was the most efficient way back then. It took me a month to come to terms with the fact that as a machine

Plan a few steps ahead. After successfully running one program, make another program with a different method. After one program is finished, run another program. Evaluate and analyze its results while another new program is running. So that if you find something that can be fixed on an earlier model, you can fix and rerun it immediately. It is also nice to have discussion with supervisor and other fellow engineers about other methods and new insight. No time is wasted regretfully.

As the data grows bigger and the methods used become more complex, a complete training process can take up to 2–3 hours. I use it as an excuse to procrastinate while the program was running and now I hate myself for that. Several times unexpected things happened, like a program error at the end of the process, a lower score than before, a memory error, and other silly errors that I just realized at the end.

My former supervisor once told me, a machine learning engineer is a software engineer and a researcher at the same time. Research is different from software engineering. We don’t stop when the system has been successfully built and is bug-free. Research is a continuous process, just keep your eyes open, there will always be new things to try.

At some point, some methods can give results with not that significant difference. Is choosing the methods which yield a slightly better result than others good enough to be the final decision? No. Many factors should have been taken into consideration. Analyzing is not just about finding out which is better from one single perspective, it is a long process.

For example, suppose you have two spam classification models whose F1 scores are 0.95 and 0.96, respectively. The second model turns out to have very low precision but high recall, while the first model has a balanced precision and recall score. In this case, the first model is better than the second because it is better at handling spam classification cases. The second model will tend to categorize a document as spam, so that more non-spam documents will be classified as spam which is something that is very fatal.

This is the kind of person who isn’t going to leave you building a narrative around your attraction, this is the kind of person that wants to write the story with you. This is the kind of person who is so serious about you, they want to be your best friend. This is the kind of person who is willing to show up, not just for dinner on a Friday, but for errands on a Tuesday, the hangover on a Sunday, your family’s get together next week.

Today I went to the Apple Store while wearing skinny jeans, and guess what? I put the phone with the MagSafe leather wallet case into my pocket and took it out of my pocket at least 20 times without the wallet falling off a single time. What was I doing differently, you may ask? I wasn’t intentionally trying to make the wallet fall off in pursuit of YouTube views.

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the level of an individual soldier the risk of error goes up massively. Orders can get misinterpreted, orders can get passed down wrong, orders can be cut off. The confusion and terror of battle could cause someone to fire a nuke without proper authorization. These nukes could be fired by a single person. Nuclear war could have come down to an accident, an itchy trigger finger or poor judgement from a low level officer.

Many of the most popular YouTube video reviews are the same: Reviewers try to put their iPhones with the MagSafe wallet in their pockets, and the magnetically attached leather wallet falls off. MKBHD and MacRumors reviews are a prime example here. The tech reviewers agreed on one thing: Using the leather wallet with MagSafe will drive you mad because it will fall off your phone every time your phone moves toward your pocket — especially if you like wearing skinny jeans. As if no one in Apple tested the leather wallet with MagSafe with skinny jeans before the wallet was released.

Jeremy Grantham is also seeing signs of euphoria in the current market which historically have been good indicators of bubbles: the flood of interest in special-purpose acquisition companies (SPACs). SPACs are also known as blank check companies are essentially large pool of cash which is listed on a public exchange with the sole purpose of completing an acquisition. Investing in SPACs according to Jeremy is based on the proposition to “give me your money and trust me I will do something useful with it”. This is a testimonial of the speculative nature of the market. Another legendary investor who thinks the market is over-valued is Warren Buffet. Through his investment company, Berkshire Hathaway, he has been sitting on more than $130 billion in cash throughout the COVID crisis.

The current stock bubble is unlike any precedented one in his view. The formation of a bubble comes from market participants unrealistically assuming that a perfect economic situation will persist indefinitely. The COVID bubble is unique in the sense that the world expects one of the worst economic conditions and yet the market is valued at historically high levels. This is his view is the direct implication from central banks across the globe injecting liquidity into the system and cutting interest rates to close to zero percent or sub-zero in some countries. He said “every dollar injected in the economy doesn’t flow through the real world but ends up fuelling asset prices or the current bubble”. There hasn’t been this much disconnect between the real world (GDP, economies) and the paper world of stocks and P/E ratios.

Jeremy Grantham is also seeing signs of euphoria in the current market which historically have been good indicators of bubbles: the flood of interest in special-purpose acquisition companies (SPACs). SPACs are also known as blank check companies are essentially large pool of cash which is listed on a public exchange with the sole purpose of completing an acquisition. Investing in SPACs according to Jeremy is based on the proposition to “give me your money and trust me I will do something useful with it”. This is a testimonial of the speculative nature of the market. Another legendary investor who thinks the market is over-valued is Warren Buffet. Through his investment company, Berkshire Hathaway, he has been sitting on more than $130 billion in cash throughout the COVID crisis.

This dilemma didn’t start with the MagSafe accessories. It is a problem that I’ve seen in tech review videos for years now, but I’ve never seen it this bad. Tech reviewers seem to have forgotten how to put stuff in their pockets.

Apple Has Been Gaslighting Us for Years The company says it created a new keyboard for the MacBook Pro because it’s ‘listening,’ but customers have been…onezero.medium.com

In October, Apple announced the iPhone 12 and iPhone 12 Pro and with them a new line of accessories called MagSafe. Apple’s MagSafe leather wallet has been getting heat ever since.