Lesson 7 In-Class Discussion

Part 1 (2018)
82

Yes, thank you for an awesome course @jeremy!

83

Thankyou @jeremy. You are awesome.

84

Looking forward to master the techniques and be much well prepared for part2ā€¦Waiting for Part2 and Thank You @jeremy and @rachel and @yinterian

85

@jeremy Thanks for all the work.
Iā€™m looking forward to continue with my training in preparation for Part 2 v2
:+1:

86

Thank you @jeremy

87

Thank you @jeremy! This is such a great class and I learned a lot. Looking forward to part 2!

88

Thank you Jeremy and Yannet for the great course!
Everyone letā€™s stick to it till the end and wait for Part 2!

89

Thank you @jeremy for the course. Course may have ended but I am going to go over the material again and again as you suggested and ofcourse come back here from time to time to help new people coming in.

2 Likes
90

Thank you @jeremy!

My only wish is that part 2 would come sooner :slight_smile: And what about a part 3? All good series come in 3s lol

3 Likes
91

Thank you @jeremy , @yinterian and everyone helping in the forums. Canā€™t wait for part 2

92

No, pls. wait. Iā€™ll some time to digest part1.

93

Big thanks to @jeremy !
I have learned a lot of cool things during part1 and cannot wait for the part2.
Plan to spend more time on techniques, pytorch and fastai source code. Especially on NLP problems.

2 Likes
94

Thank You @everyone for making things look simplerā€¦

95

Thank you @jeremy @yinterian for this course. Todayā€™s lecture was my favourite. Will definitely have to watch these 2 more times to completely assimilate the material. Big thanks to @timlee too for his course notes which helped out a lot.

2 Likes
96

Thank you @jeremy, @yinterian!

97

In medical images , sometimes higher resolution images are provided because it is available , for example there was a kaggle competition on retinopathy that deals with diabetes - there high resolution of iris scan was available .
My question is - does higher number of blocks help to obtain higher accuracy in case of high resolution images (3000px x4000 px) - or low number of resnet block is good enough.

2 Likes
98

Thank you @jeremy and @yinterian! Your work is very much appreciated! Weā€™d love to help you make fastai the best framework out there!

99

Thank you @yinterian, @jeremy , and the forum community! It is still sinking in for me, but I canā€™t wait for part 2!

100

Thank you @jeremy @yinterian! Hoping to continue learning and being part of this community !

101

@jeremy - Thank you for teaching this course and especially for your words of encouragement for people new to deep learning. Thanks forum friends for asking and answering so many excellent questions.

1 Like