Plain and Simple Estimators 

this video was created with tensorflow V 1.3.0, todays version is 2.9.1. contrib is removed. please consider updating the video.

Yufeng, your job is really good in having these videos to teach ML for people. My only advice is to number the videos, so that people like us in Africa will find it easy to follow the videos to learn ML/AI

Hi Yufeng, great video. However, when I tried to code it by hand, or even use the notebook you supplied, I realised that my Tensorflow is version 1.1 instead of 1.3 that you have. And this is in January 2018. Secondly, for a novice, you left out the data files needed for this short exercise. Yes, I understand that this is supposed to be a quick (and dirty) intro. However, the data that I downloaded, has not been wrangled yet. As you use numeric targets, instead of the flower name, can you explain which flower you assigned the value 0, 1 and 2. Lastly, the code to to load the training data does not work, which I suspect has to do with the Iris data file I downloaded from the wiki website. The data preparation is important, and you have left out this stage and not let us know this part of the workflow. Nonetheless, I truly enjoy the series of videos you have created. Thank you.

Excellent. Brief. Clear. Thoughtfully highlighted and focused presentation. Mr. Guo easily understood.

Hello, I have watched your videos and I like it. I try the code in my computer but my TensorFlow version is 2.0 so there is no .contrib module anymore, do you know what module can I use in my TensorFlow?

Hello I really appreciate your job :) I wish if you use little examples for each step and be little slower please.

very nice video greate to learn machine learning in simple way

for thos interested in grabbing the actual csv files he's referencing in this video they are at the following url: - download.tensorflow.org/data/iris_training.csv - download.tensorflow.org/data/iris_test.csv Thank you Google for this insightful ML tf video.

this material is outdated!!!

Awesome Playlist!

Whats the best way to start to get familiar with what is explained in the video? Thanks!

Very good job !!! Its first time that understand the ML Please go on

We did the same example in Multivariate Analysis. Really concise and simple to follow video. But how would we do it using images?

Wondeful. Looking forward to using Tensor flow soon.

Does base.load_csv_with_header takes target as the last column of the table in : base.load_csv_with_header(filename=IRIS_TRAINING, features_dtype=np.float32, target_dtype=np.int)

Heres the datasets :) download.tensorflow.org/data/iris_test.csv download.tensorflow.org/data/iris_training.csv

It seems that the sessions run through a Estimator are not quite the same as a normal session? For example, `.eval.()` operation and the `tf.nn.sampled_softmax_loss` function do not work, when they do for a normal session. Would love to hear some details on this phenomenon.

This is quite a nice intro to ML. I like the idea.

So basically we need to convert the Species column to integers? When watching this tutorial, somehow I feel like that the csv loading function will convert them into factors by default. If a conversion is required, why isn't the processed data provided for downloading? Thanks

I cannot grasp the term classifier. Can you elaborate on this term please? Thank you!

Very nice intro to ML

As some of the functions have become deprecated, can you please update the code? Also, I couldn't find the documentation of tf.estimator.LinearClassifier. Can you please provide the link of the documentation?

How do you predict, given a single feature (e.g. [6.4, 3.2, 4.5, 1.5]) using classifier.predict()?

Awesome series!!! Thanks a lot.

Is it important to know Tensor Flow and Python Pytorch? Which is more popular and being used by companies in the work force ? Thanks

Why do not work with the cost function in this example?

How do you create a prediction based on this model ?

AWESOME! thanks for this video series.

******** from tensorflow.contrib.learn.python.learn.datasets import base # Data files IRIS_TRAINING = "iris_training.csv" IRIS_TEST = "iris_test.csv" ******** I thought above code would bring in the training and test data . I get this error NotFoundError: NewRandomAccessFile failed to Create/Open: iris_training.csv : The system cannot find the file specified. ; No such file or directory looks like a great class, but cannot follow on my Jupyter notebook.

Great but could your help me what information i have to study to deeper understand it all?

Hi, thanks for the videos. I am new at AI and ML. I am trying to make practice with python 3 as possible as I can. This sample witch you show in the video give me an unexpected error. Where can I put the screan? I cant find an answer online.

what programming language will we use to write that code

nice series.. looking forward to watch the new video 👍🏻

I converted data, now the csv looks like 6.7,3.3,5.7,2.5,0 6.7,3,5.2,2.3,1 6.3,2.5,5,1.9,2 ... training_set = base.load_csv_with_header(filename=IRIS_TRAINING, features_dtype=np.float32, target_dtype=np.int) ValueError: invalid literal for int() with base 10: 'Sepallength' any tip?

Great video! Just one thing, Im using python 3.6 but when reaching the part of code "classifier = tf.estimator.LinearClassifier" it gives me this error "AttributeError: module 'tensorflow.python.estimator.estimator_lib' has no attribute 'LinearClassifier'"

Is there any demo with javascript?

Great job,man!

That code is very difficult to understand....If you can explain the code,it would help

I followed this example and it works great BUT... I wanted to predict some values, lets say: [6.4, 3.2, 4.5, 1.5] How can I do that? I tried several ways using classifier.predict() but always got errors. Do someone know how to code a "single" prediction? (please give a working example!)

In addition to knowing AI programming and Python what other languages should we have know for obtaining a job. As a beginner

Where to download the CSVs? Can anybody tell me how to do that?

Fantastic!

it would be great if you could explain all lines of code @gcp

Ugh. The tensorflow.contrib module is redundant now. Sad times

Does this example work with Python3?

I am not sure if I should say I understood. I appreciate your efforts, sadly for a new bee , it could be a hard time understanding what you just taught. You might want to split up the topic into multiple videos and explain elaborately. Nevertheless, your efforts are appreciated.

Finally... The place to learn ML :)

Thanks very much for the explanation boy!

Is this still up-to-date?

Wow... superb

amazing

do we need python 3 for this?

Nothing understood. I thought this series would be useful but.... not able to understand what you are doing. where's the code to copy and how to download data. Actually are we supposed to do the same thing you did in the video or just watch it

great video.

Went to the jupyter notebook and typed what he typed and it didn't work.

I am eager to learn ML and UI desinging.. I am in progress of creating my own Web app that helps in education. I am a beginner to ML suggest some books, vidoe link, tutors . to make me better.

Hi can you show a video in detail about this program as I am new in python

can you give me iris_traing csv file and also test file

1. Please show how to predict exported model on PC. 2. Please show how to predict model on PC without exporting.

Sir, can u share Ur codes in github. please provide a Github link.

I'm looking forward to the video that shows the classifiers working in real time e.g. I upload an image and the classifier immediately tells me hot dog | not hot dog.

Sir, i want to learning very basic level machine learning and AI.

Cool grea

Neat

smart guy

I enrolled into EITC AI certification, I have been trying to run this example for two days and... I received a nice welcome to tensorflow. This is full of deprecated code, and replacing it is a PITA. The documentation is a mess, this example is lost in history and it's time for an update... that will also be temporary anyway . What a crappy way to mantain a codebase, and making examples on a tutorial video based in a temporary-meant-to-be-removed "contrib" namespace is very nerdy and amateurish to say the least.

estimator is a terriable design

I guess this is definitely not for the beginners who is absolute beginner.

牛逼啊！各方面都牛逼！

No hate but you know what they say, the lower the V the smaller the D. HAHA cheers, great video