糖心vlog官网观看

The video's are voiced by a robot. There is alot of information, but the quiz questions are so simple that you get the feeling they are aimed at 6-year olds (e.g. most times you just have to repeat what the robot voice has JUST said). The peer review system for the honors assignment is retarded: I failed this assignment while answering everything correctly, just because some dude accidentaly misgraded a question. 糖心vlog官网观看 now expects me to pay another 40 euros to resubmit the assignment just because someone else messed this up, lol. Take your courses elsewhere.

Practice sessions are organized in a tool that doesn't have enough computing power for training neural networks. The networks often take hours to train and you have to constantly monitor them because if you don't, the tool will automatically sign you out and you will lose your results.

I also don't like the mechanistic reading style (sounds like a bot reading), lack of human interaction doesn't seem to work for lectures.

Poorly prepared materials, awful quiz modules, lots of mistakes

Good course but unfair final test (Discriminationon: Only USA credit card holders can access the test on IBM Cloud): The course for PyTorch by IBM requires an IBM account to log into IBM Cloud for the final test. During registration, I have to provide my payment card to IBM. However, I can't register an account with either of my credit cards from Germany. It says, "please contact IBM Service, there is a problem identifying your card." From the comments, someone else also has this problem, and the teacher has said to either use a credit card from the USA or wait for a feature code issue. Why can't you provide the test on the 糖心vlog官网观看 platform online, like other courses on 糖心vlog官网观看, even like other courses from IBM on 糖心vlog官网观看? It's very frustrating that I cannot take the test due to IBM's error. I suggest canceling this course because of discrimination.

Bad !!!!! Many mistakes, questions too easy !!! I am really disapointed

Amazing course with brilliant explanation

It was well structured . Thank you

Good!

The course is interesting and well organized but the quiz are not challenging and full of typos.

Useful if you are already comfortable with deep learning and you want to learn how to use the (great) pytorch package. If you want to learn about deep learning from scratch, the explanations are not very intuitive and skip over some very interesting features.

Awful quality content that fails to teach or test you properly.

The videos are exceptionally poor using a text-to-speech narrator that makes you want to quit after only one video. Additionally, the quizzes are buggy with awful wording, typos, invisible options, and useless content. The biggest shame is that they don't use notebooks to test your learning with real examples that would reinforce both the theory & practical elements.

This course has no effort put into it & is clearly a money grab. Avoid this and instead try a deeplearning.ai or fast.ai course.

I had very high expectations for this course since it was offered by IBM and being taught by someone with excellent credentials. I completed the course material for the first 2 weeks and I found the lectures to me unmotivating, inadequately explained, and very clearly the lecturer read from a script. Important concepts were not explained neither the conceptual deep learning one nor the PyTorch programming ones. They were very briefly explained often with one short sentence. I thought the ungraded labs were very well designed but the lecture quality was so poor, it seemed I was just googling and learning 90% of PyTorch myself. I had expected quality from this course however, I did not get it so I decided not to pay the $50 subscription and canceled the course. I was disappointed since I did spend good 15-20 hours on this course.

This course is a disorganized and unfocused. For example, much of the section on Bernoulli distribution is misleading or completely incorrect. It's also presented without context. Much of this is redundant give the other courses in this certificate program do a much better job of teaching ML concepts. The novelty of this course is about implementation using pytorch and most of the important details about how to use PyTorch and why certain parameters are used are glossed over.

Is this a course about ML and Neural Networks? Is this a course on PyTorch? It does both poorly.

Please see

/mastertrack/instructional-design-illinois

for how to improve.

Learning content was good, but making assignments was a nigthmare, I could not set up an IBM Cloud account, becasue they could not verify my payment card, when i asked them to help me, they just responded "We have reviewed your account/transaction and will not be able to offer services. No further information will be disclosed regarding this matter. Any card authorizations will reverse within 24-72 hours depending on the issuing bank.". They ghosted me completely and did not want to help. I do not recommend. It's no wonder that with this kind of customer attitude IBM is far behind the competition today.

The course is extremely slow and low level. Some important information on the slides might be around for less than a second, whereas unimportant information might be repeated several times. There is too many quite similar labs and very few background information. The practice parts and even the final assignment are way too simple.

At least, it seems one is able to learn some basic notion of PyTorch,

Carelessly written and designed; lots of errors in videos (I think it was AI-generated) and the quizzes were a joke. Half the time there were spelling and grammatical errors which caused difficulty with understanding what was being asked. Some choices of answers also were just "incorrect" rather than actual giving an option for an incorrect answer.

This course is really good in explaining the concepts and pytorch. Everything was explained in a detailed way, well structured. However, I found the course too segmented. Some lectures, some quizzes, and some labs can be combined. Example for week 1, I think 1.1 (introduction to tensors), 1.2 (1d tensors) and 1.3 (2d tensors) can be combined to single lecture or all 3 lectures be one after another making it appear like it鈥檚 together. The 2 labs can be combined into a single notebook. The 2 quizzes can be combined into 1 quiz of maybe 5 or more questions. Similarly, 1.4 (Simple Datasets) and 1.5 (Datasets) can be combined, and so on. I also think that the honours content about batch normalization should be included as part of normal contents. Maybe more advanced concepts can be put up as honours contents.

袣褍褉褋 "Deep Neural Networks with PyTorch" 锌芯写褏芯写懈褌 写谢褟 薪芯胁懈褔泻芯胁, 谢褞写械泄 褋 斜邪蟹芯胁褘屑 屑邪褌械屑邪褌懈褔械褋泻懈屑 邪锌锌邪褉邪褌芯屑, 褋 斜邪蟹芯胁褘屑懈 蟹薪邪薪懈褟屑懈 锌褉芯谐褉邪屑屑懈褉芯胁邪薪懈褟 Python 懈 写谢褟 褌械褏, 泻芯谐芯 懈薪褌械褉械褋褍械褌 屑邪褌械屑邪褌懈泻邪 薪械泄褉芯薪薪褘褏 褋械褌械泄 懈 屑邪褕懈薪薪芯谐芯 芯斜褍褔械薪懈褟. 袣褍褉褋 写械谢邪械褌 褍锌芯褉 薪邪 褋邪屑芯褋褌芯褟褌械谢褜薪芯褋褌褜 芯斜褍褔邪褞褖懈褏褋褟 懈 谢褞写械泄, 泻芯褌芯褉褘械 褋邪屑懈 蟹邪懈薪褌械褉械褋芯胁邪薪褘 胁 锌褉芯褏芯卸写械薪懈懈 谢邪斜芯褉邪褌芯褉薪褘褏 褉邪斜芯褌. 袟写械褋褜 械褋褌褜 屑薪芯谐芯 懈薪褋褌褉褍屑械薪褌芯胁 写谢褟 芯斜褍褔械薪懈褟, 胁褘褔懈褋谢械薪懈褟 屑械褌褉懈泻, 胁懈蟹褍邪谢懈蟹邪褑懈懈 褉械蟹褍谢褜褌邪褌芯胁, 泻芯褌芯褉褘械 屑芯谐褍褌 锌褉懈谐芯写懈褌褋褟 袙邪屑 胁 锌褉芯械泻褌邪褏. 袣褍褉褋 锌褉械泻褉邪褋薪芯 锌芯写褏芯写懈褌 写谢褟 谢褞写械泄 褋芯 褋褉械写薪懈屑 蟹薪邪薪懈械屑 邪薪谐谢懈泄褋泻芯谐芯 褟蟹褘泻邪 (屑邪褌械褉懈邪谢 褉邪蟹褉邪斜芯褌邪薪 褌邪泻, 褔褌芯 芯薪 锌芯薪褟褌械薪 懈 谐谢邪蟹邪屑, 懈 褍褕邪屑). 小芯胁械褌褍褞 锌褉芯泄褌懈 写邪薪薪褘泄 泻褍褉褋 薪邪 邪薪谐谢懈泄褋泻芯屑 褟蟹褘泻械 懈谢懈 褋 邪薪谐谢懈泄褋泻懈屑懈 褋褍斜褌懈褌褉邪屑懈, 褔褌芯斜褘 锌芯谐褉褍蟹懈褌褜褋褟 胁 懈蟹褍褔械薪懈械 PyTorch 懈 锌褉芯褎械褋褋懈芯薪邪谢褜薪芯泄 褌械褉屑懈薪芯谢芯谐懈懈 褉邪蟹褉邪斜芯褌褔懈泻芯胁.

I really liked this course, which gradually, in detail, step by step, reveals the capabilities of PyTorch, and the neural networks implemented on its basis.

The IBM trainers have put a lot of effort and experience into the preparation of the course materials. Thank you very much!!!

PyTorch is the best for constructing neural networks, this course goes very deep into the construction of neural networks. It also gets into some of the mathematical details which is always good. Thank you 糖心vlog官网观看, IBM and Mr Sartancangelo!

even with no mandatory peer graded assignment, for me it was the hardest course to learn in "IBM AI Engineering". So many topics and so many codes to check for each week. i liked it. i believe i will revisit the materials in the future.

Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.

Not only did I gain the basic knowledge of deep learning, but also learned Pytorch. It is a good course, however, there is still a lot more to go in the area of Deep learning,

While there are some minor technical issues loading out of date libraries, the material and subjects are incredibly useful. This course is very difficult and welcome

The explanation is simple and understandable. They explained deep neural networks so beautifully with PyTorch. Thank you very much for this course IBM.