Machine Learning Training Classes in Chattanooga, Tennessee
Learn Machine Learning in Chattanooga, Tennessee and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current Machine Learning related training offerings in Chattanooga, Tennessee: Machine Learning Training
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Blog Entries publications that: entertain, make you think, offer insight
The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.
Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.
Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.
Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.
This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.
Related:
Anonymous reprint from Quora (career advice)
Occasionally we come across a unique profound perspective that makes one stop and really listen. The following advice is one such as this.
- Small actions compound: Reputation, career trajectory, and how others perceive you in the workplace can come down to a handful of things/moments that seem inconsequential/small at the time but compound. Random Thought: Redwood trees come from small seeds and time. With every action you're planting small seeds and these seeds can grow into something bigger (sometimes unimaginably bigger) over time. Don't let small basic mistakes sabotage your reputation because it only takes a few small snafus for people to lose confidence/trust in your ability to do more important tasks. Trust is a fragile thing and the sooner people can trust you the faster they'll give you more responsibility. Some Examples: Being on time (always) or early (better); spending an extra 10-15 minutes reviewing your work and catching basic mistakes before your boss does; structuring your work so it's easy for others to understand and leverage (good structure/footnotes/formatting); taking on unpleasant schleps/tasks (volunteer for them; don't complain; do it even when there's no apparent benefit to you)
- Rising tide lifts all boats: Fact: You don't become CEO of a multi-billion dollar public company in your 30s based purely on ability/talent. Your career is a boat and it is at the mercy of tides. No matter how talented you are it's a lot harder to break out in a sluggish situation/hierarchy/economy than a go-go environment. Even if you're a superstar at Sluggish Co., your upside trajectory (more often than not) is fractional to what an average/below average employee achieves at Rocket Ship Co. There's a reason Eric Schmidt told Sheryl Sandberg to "Get on a Rocket Ship". I had colleagues accelerate their careers/income/title/responsibility simply because business demand was nose bleed high (go go economy) and they were at the right place at the right time to ride the wave. Contrast that to the 2008 bust where earnings/promotions/careers have been clamped down and people are thankful for having jobs let alone moving up. Yes talent still matters but I think people generally overweight individual talent and underweight economics when evaluating/explaining their career successes. Sheryl Sandberg Quote: When companies are growing quickly and they are having a lot of impact, careers take care of themselves. And when companies aren’t growing quickly or their missions don’t matter as much, that’s when stagnation and politics come in. If you’re offered a seat on a rocket ship, don’t ask what seat. Just get on.
- Seek opportunities where the outcome is success or failure. Nothing in between! You don't become a star doing your job. You become a star making things happen. I was once told early in my career that you learn the most in 1) rapidly growing organizations or 2) failing organizations. I've been in both kinds of situations and wholeheartedly agree. Repeat. Get on a rocket ship. It'll either blow up or put you in orbit. Either way you'll learn a ton in a short amount of time. Put another way; seek jobs where you can get 5-10 years of work experience in 1-2 years.
- Career Tracks & Meritocracies don't exist: Your career is not a linear, clearly defined trajectory. It will be messy and will move more like a step function.
- You will probably have champions and detractors on day 1: One interesting byproduct of the recruiting & hiring process of most organizations is it can create champions & detractors before you even start the job. Some folks might not like how you were brought into the organization (they might have even protested your hiring) and gun for you at every turn while others will give you the benefit of the doubt (even when you don't deserve one) because they stuck their neck out to hire you. We're all susceptible to these biases and few people truly evaluate/treat folks on a blank slate.
- You'll only be known for a few things. Make those labels count: People rely on labels as quick filters. Keep this in mind when you pick an industry/company/job role/school because it can serve as an anchor or elevator in the future. It's unfortunate but that's the way it is. You should always be aware of what your "labels" are.
- Nurture & protect your network and your network will nurture & protect you: Pay it forward and help people. Your network will be one of the biggest drivers of your success.
The original article was posted by Michael Veksler on Quora
A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.
The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.
Readability is a tricky thing, and involves several aspects:
- Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
- Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
- Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
- Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
- Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
- Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
- As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
- The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.
Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.
Don’t blindly use C++ standard library without understanding what it does - learn it. You look at
documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::vector::push_back()
, and with std::map
. Knowing the difference between these two maps, you’d know when to use each one of them.std::unordered_map
Never call
or new
directly, use delete
and [cost c++]std::make_shared[/code] instead. Try to implement std::make_unique
yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.usique_ptr, shared_ptr, weak_ptr
Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.
Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.
Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.
Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.
These are the most important things, which will make you a better programmer. The other things will follow.
In Python, the following list is considered False:
False, None, 0, 0.0, "",'',(),{},[]
Tech Life in Tennessee
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
First Horizon National Corporation | Memphis | Financial Services | Lending and Mortgage |
Vanguard Health Systems, Inc. | Nashville | Healthcare, Pharmaceuticals and Biotech | Hospitals |
The ServiceMaster Company | Memphis | Consumer Services | Consumer Services Other |
Eastman Chemical Company | Kingsport | Manufacturing | Chemicals and Petrochemicals |
Brookdale Senior Living, Inc. | Brentwood | Healthcare, Pharmaceuticals and Biotech | Residential and Long-Term Care Facilities |
Scripps Networks Interactive | Knoxville | Media and Entertainment | Radio and Television Broadcasting |
Dollar General Corporation | Goodlettsville | Retail | Retail Other |
IASIS Healthcare Corporation | Franklin | Healthcare, Pharmaceuticals and Biotech | Hospitals |
Thomas and Betts Corporation | Memphis | Energy and Utilities | Gas and Electric Utilities |
Tractor Supply Company, Inc. | Brentwood | Retail | Clothing and Shoes Stores |
TeamHealth, Inc. | Knoxville | Healthcare, Pharmaceuticals and Biotech | Doctors and Health Care Practitioners |
UNIVERSITY HEALTH SYSTEM, INC. | Knoxville | Healthcare, Pharmaceuticals and Biotech | Hospitals |
Corrections Corporation of America | Nashville | Business Services | Security Services |
AutoZone, Inc. | Memphis | Retail | Automobile Parts Stores |
Mueller Industries, Inc. | Memphis | Manufacturing | Metals Manufacturing |
UNUM Group | Chattanooga | Financial Services | Insurance and Risk Management |
Fred's, Inc. | Memphis | Retail | Grocery and Specialty Food Stores |
International Paper Company | Memphis | Manufacturing | Paper and Paper Products |
Regal Entertainment Group | Knoxville | Media and Entertainment | Motion Picture and Recording Producers |
Genesco Inc. | Nashville | Wholesale and Distribution | Apparel Wholesalers |
Cracker Barrel Old Country Store, Inc. | Lebanon | Retail | Restaurants and Bars |
Lifepoint Hospitals Inc. | Brentwood | Healthcare, Pharmaceuticals and Biotech | Hospitals |
FedEx Corporation | Memphis | Transportation and Storage | Postal, Express Delivery, and Couriers |
Community Health Systems | Franklin | Healthcare, Pharmaceuticals and Biotech | Hospitals |
HCA Holdings, Inc. | Nashville | Healthcare, Pharmaceuticals and Biotech | Hospitals |
HealthSpring Inc. | Franklin | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
training details locations, tags and why hsg
The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:
- Learn from the experts.
- We have provided software development and other IT related training to many major corporations in Tennessee since 2002.
- Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
- Discover tips and tricks about Machine Learning programming
- Get your questions answered by easy to follow, organized Machine Learning experts
- Get up to speed with vital Machine Learning programming tools
- Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
- Prepare to hit the ground running for a new job or a new position
- See the big picture and have the instructor fill in the gaps
- We teach with sophisticated learning tools and provide excellent supporting course material
- Books and course material are provided in advance
- Get a book of your choice from the HSG Store as a gift from us when you register for a class
- Gain a lot of practical skills in a short amount of time
- We teach what we know…software
- We care…