TensorFlow high-level APIs: Part 1 - loading data

[@wrightw1982]

Super helpful series. Doesn't just tell you how to build SOME PARTICULAR model, but how to build any basic/canned model. Best mini-tutorial I've seen so far.

[@mdrayedbinwahed2172]

Typo in 5:24. 'row_vals' should be 'vals'

[@TerenceChill286]

Thanks for that. I was wondering were the row_vals came from

[@thinkforsociety]

You are rite

[@MikeDownes]

Thanks this was incredibly well put together easy to understand and so so useful.

[@bhesht]

Immaculately described and concise at once. Thank you!

[@andrassteger9589]

A lot of changes happened in the last 3 years. Maybe some update would be appreciated :-) Thank You!

[@gowthamkumar3296]

In Tensorflow updated versions, numpy is removed from tensor, then how we will extract value from that tensor

[@soumyodey1795]

There is a big mistake in the code shown in the video. The function _parse_csv_rows() is incorrect, it should be def _parse_csv_rows(*vals): soil_type_t = tf.convert_to_tensor(vals[14:54]) feat_vals = vals[:10] + (soil_type_t, vals[54]) features = dict(zip(col_names_features, feat_vals)) class_label = tf.argmax(vals[10:14], axis=0) labels = {col_names_label: class_label} return features, labels where col_names_features, col_names_label are col_names_features = [ "Elevation", "Aspect", "Slope", "Horizontal_Distance_To_Hydrology", "Vertical_Distance_To_Hydrology", "Horizontal_Distance_To_Roadways", "Hillshade_9am", "Hillshade_Noon", "Hillshade_3pm", "Horizontal_Distance_To_Fire_Points", "Soil_Type (40 binary columns)", "Cover_Type (7 types)" ] col_names_label = "Wilderness_Area (4 binary columns)"

[@qiyang1247]

What can we do to solve the problem of memory leaking when cooperating tf.keras with tf?

[@nunodias8927]

Many things to do only for read a datafile. It will be more easy do a function to aggreate all possibilities and the end user set the options in according with your own needs. In fact this demo is useful only if you knows the structure of your data. If you can not open the file with a simple editor you don't know the structure of your data, so you can not setup TF to read the data if you do not know the structure of the data.

[@sachavanweeren9578]

There is a bug in the code snippet on Parsing data - 'row_vals' is not defined, this should be replace by ' vals' . Better to share working code and provide links with the video.

[@BadriNathJK]

Can you tell me how to get each token vector when using both feature column and TF HUB? Because feature column gives average of token vector in a sentence. I am struck with the problem now

[@mounkailagarba9952]

Very good presentation

[@neerajgobari9748]

How can I use model final output to compute a prediction..so that I can compare prediction to ground truth value to compute loss function and fine tune my model

[@fahemhamou6170]

تحياتي الخالصة شكرا جزيلا

[@tingnews7273]

great vedio. Finally tensorflow make some vedio I can unstand. Good job

[@TheIsrraaa]

good vedio

[@claudee8736]

Building a ML Model is a multi-stage process = kzbin.info/www/bejne/pXepk36lnL6XnMU 1. Collect data, clean data and process data 2. Prototype and iterate on model arquitecture 3. Train and evaluate results 4. Prepare your model for production serving 5. Repeat all over again

[@aonoymousandy7467]

my csv files have a string at the end of each row, and this is causing error in my code, how would I setup defaults to account that I have a row of 10 floats and the very last feature is a string?

[@write2sekhar]

Good and well presented looking for coode and examples.

[@simplysmile8573]

github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@huqiao]

This is not a very good example as you were using tf.contrib which will soon be deprecated in TensorFlow 2.0.

[@shionwill7095]

Please share your code and the data so that we can follow along this great tutorial!

[@simplysmile8573]

data example and code : github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@xkcd_68868]

Is this for Tensorflow 2.0?

[@nathanas64]

Excellent presentation!

[@anubhav114]

hello, thanks for the wonderful explanation of tensorflow usage. Could you please point me to the guide for i/o optimization @5:51 ?

[@nvrgr]

Good one, Karmel!

[@mounkailagarba9952]

Thank you very much

[@Mrduirk]

un csv puede contener imagenes?

[@hixenP]

Karmel are you sitting down while making this video? JW 😊

[@fusedglass01]

Is this supposed to be TF 2.0? when I issue a print version I get "tensorflow_core._api.v2.version'". Unbelievable how much pain these guys cause, by changing stuff every release. Google... can you please Google the term "backwards compatibility?" I'm just trying to read in a two column csv. I agree it looked great while I was watching it, but its next to useless when I get errors about contrib and enable_eager arnt part of the tf module. Guys please release more of this style, but add more detail around what versions you need and at the end show us 100% of the code.

[@AbhishekKumar-mq1tt]

Thank u for this awesome video

[@shaktirajsinhjadeja7386]

Hi , Great video to learn from :) Will it be possible to get the access of dataset ?

[@simplysmile8573]

data example and code: github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@JeremAl]

Hi, great tutorial! Any chance to have the code? I am STRUGGLING to start with the data set!!! (8hours later... :( )

[@willtun5385]

SAME! ME WANT GITHUB CODE!

[@simplysmile8573]

data and code : github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@eilaorielresearch1205]

tf.contrib.data.CsvDataset is planned to be deprecated. the new API will be tf.data.experimental.CsvDataset

[@username42]

where are the codes sources?

[@RahulSingh-ln7bg]

highly confusing demo

[@kaan-tube]

this probably assumes some level of python knowledge. if you don't know what a dictionary is or what the zip function do, I can see how this might get complicated.

[@deeplearningpartnership]

Very interesting.

[@kevinlieb]

Please point us to the code and the demo data.

[@meeexy116]

tf.contrib is deprecated now.

[@joryhansen50]

why isn't contrib in TF2.0????

[@RARa12812]

this is tensorflow 1.0 correct?

[@andreamarkos]

how about a little bit of API sugar here?

[@sushilchauhan7660]

Good tutorial but no git hub link here to view code

[@mladenradosevic5333]

mini-series on TensorFlow high-level APIs! In this 3 part mini-series is in wrong order ... first (I presume should be part 1, not part 3

[@balajichetty305]

Github code ?

[@obsiyoutube4828]

please i need code and dataset?good presentation

[@simplysmile8573]

data and code example here : github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@mdrayedbinwahed2172]

Github?

[@pabloe1802]

Use tf.data.experimental.CsvDataset

[@yonimalka6954]

I have created a notebook to follow the video along if anyone is interested: gist.github.com/malkayo/71e483c6f234dd5aca0eaaa52a5c24e0

[@chrischoir3594]

Way too much work for something so basic

[@arkarnyanhein]

you don't show step by step how you import the data gg. GG engineer

[@stumpy1495]

This should be removed or updated, there is no contrib within TF 2.x

[@ayasalama7965]

Very confusing

[@nandagopalgopakumar5626]

FIRST :P

[@zdenes]

Please share your code and the data so that we can follow along this great tutorial!

[@AZTECMAN]

data: www.kaggle.com/uciml/forest-cover-type-dataset

[@simplysmile8573]

data and code : github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb

[@johndoucette3687]

@@simplysmile8573 This link does not seem to have anything to do with this video.

[@simplysmile8573]

@@johndoucette3687 it is the code implementation of what is discussed in the video. This might help follow the tutorial. I hope this helps.

[@simplysmile8573]

​@@johndoucette3687 I see your point though. Well, the dataset that is being used might matter less than the actual computation and ability to reproduce the learning pipeline. It is not about forest coverage but about how to preprocess, analyse and build an algorithmic pipeline. The aim of the link is to show the pipeline that does similar thing (though the dataset is different). Feel free to use the forest coverage dataset to replace the dataset used in the link and it will be fine. Best Regards.

[@tameribrahim7831]

Please share your code and the data so that we can follow along with this great tutorial!

[@simplysmile8573]

github.com/adderbyte/Tensorflow_Tutorials--tf.Slim_GPU_included/blob/master/NewFeaturesTF/TF_DATA_API/Illustrtation_For_Tensorflow2.ipynb