Things like "insults, and a legal demand letter" are very concerning because they're threatening you. Those things aren't normal responses. You should consider hammering that nail in civil court because they're damaging your reputation.
It seems like a lot of new consultants don't understand the differences between working as a 1099 contractor vs. W2 contractor vs. regular employee. I've met plenty of people who mistake a W2 contractor as the same as a regular employee except that the work is temporary.
I would like to point out that W2 contractors should expect their performance to be evaluated by the hour because that's the rate the client is being is charged for solutions. That's why it's important for W2 contractors to work only during normal business hours so that the client can't claim (later when payment is due) that the client didn't have opportunity to approve of said work and evaluate said work when the contractor delivered solutions to them.
I'm working toward moving my deep learning project DeepSentry into e-commerce. DeepSentry was developed in Python3 and C. After any significant amount of time 60+ days the dataset per host is TB-PB. So, I've been digging into implementing a Big Data solution. I've found that Apache Spark on Hadoop-MapR with Postgres is popular.
Which projects you know use "disk, S3, github,..." to share their datasets? I'm curious what you think because I haven't read about any ML projects actually using hosted ML solutions like Amazon ML+S3. I've only seen Amazon recommend Amazon ML.
I'm just saying that I think a lot of young people in the tech industry don't care about work-life balance. And those same young people wouldn't have a problem working 12 hours a day to complete a project.
Secondly, highly talented professionals do spend free time practicing their skills. Idk anything about surgeons.
I'm in tech because I think the work is fun. I'm typically on my computers up to 18 hours a day. As you can imagine I would have no problem doing some r&d after hours for fun.
Who cares what other professions are doing? I'm in tech because I'm a builder and that's what I care about.
I think that the younger workers in their 20's to 30's, especially the new tech workers, are really doing it because it's fun. So, working 12 hours a day 6-7 days a week isn't a big deal. Whereas the older crowd, the 40+'ers, want the same pay (or more) for 'work-life balance'. I've been told 'work-life balance' means up to 8 hours a day and up to 5 days a week, and after hours is for spending time with family and friends.
I've encountered plently of 40+'ers who discourage learning new skills during free time, programming on the weekends, hackathons, and the like. Simply because that stuff goes against work-life balance.
It's hard for me to believe that the 40+'ers are as ambitious as younger tech workers.
I haven't read much about XGBoost boosted trees. Does each tree have additive independence? Is the tree ensemble of two trees better than one tree?
It seems like additive training that removes all constants in addition to regularization of model complexity would shape the tree ensemble into a baseline model that defines minimum assumptions. So, what's its success rate in predicting favorable outcomes vs. tree learning focused on heuristic specialization (impurity)?