This is the index page of the “How to solve Classification Problems in Deep Learning with TensorFlow & Keras?” tutorial series.

We will cover all the topics related to solving Classification Problems with sample implementations in Python TensorFlow Keras.

You can access the codes, videos, and posts from the below links.

If you would like to learn more about Deep Learning with practical coding examples, please subscribe to the Murat Karakaya Akademi YouTube Channel or follow my blog on Medium. Do not forget to turn on notifications so that you will be notified when new parts are uploaded.

Last updated…


Author: Murat Karakaya
Date created: 21 April 2021
Last modified: 24 May 2021
Description: This is an introductory tutorial on Controllable Text Generation in Deep Learning which is the second part of the “Controllable Text Generation with Transformers” series
Accessible on:

Photo by Chris Leipelt on Unsplash

Controllable Text Generation with Transformers tutorial series

This series will focus on developing TensorFlow (TF) / Keras implementation of Controllable Text Generation from scratch.

Part A: Fundamentals:

  • A1 Fundamentals of Text Generation
  • A2 Fundamentals of Controllable Text Generation

Part B: A Tensorflow Data Pipeline for Word Level Controllable Text Generation

Part C: Sample…


INDEX PAGE: This is the index page of the “tf.data: Tensorflow Data Pipelines” series.

We will cover all the topics related to tf.data Tensorflow Data Pipeline with sample implementations in Python Tensorflow Keras.

You can access the codes, videos, and posts from the below links.

If you would like to learn more about Deep Learning with practical coding examples, please subscribe to my YouTube Channel or follow my blog on Medium. Do not forget to turn on notifications so that you will be notified when new parts are uploaded.

Photo by Florian Wächter on Unsplash

MEDIUM BLOG LINKS:

Part A: tf.data: Build Efficient TensorFlow Input Pipelines for Image Datasets

Part B: Building an Efficient TensorFlow Input Pipeline for Character-Level Text Generation

Part C


Author: Murat Karakaya
Date created: 21 April 2021
Last modified: 19 May 2021
Description: This is an introductory tutorial on Text Generation in Deep Learning which is the first part of the “Controllable Text Generation with Transformers” series

Accessible on:

Photo by Markus Spiske on Unsplash

Controllable Text Generation with Transformers tutorial series

This series will focus on developing TensorFlow (TF) / Keras implementation of Controllable Text Generation from scratch.

You can access all the parts from this link or the below post.

Important

Before getting started, I assume that you have already reviewed:


This is the index page of the “All About LSTM in Tensorflow & Keras” tutorial series.

We will cover all the topics related to LSTM with sample implementations in Python Tensorflow Keras.

You can access the codes, videos, and posts from the below links.

You may also like to check out the SEQ2SEQ (SEQUENCE TO SEQUENCE) Learning tutorial series in which LSTM layer has been used heavily.

If you would like to learn more about Deep Learning with practical coding examples, please subscribe to the Murat Karakaya Akademi YouTube Channel or follow my blog on Medium. …


This is the index page of the “Controllable Text Generation in Deep Learning with Transformers (GPT3) using Tensorflow & Keras” tutorial series.

We will cover all the topics related to Controllable Text Generation with sample implementations in Python Tensorflow Keras.

You can access the codes, videos, and posts from the below links.

You may like to start with learning the Text Generation methods in Deep Learning with Tensorflow (TF) & Keras from this tutorial series.

If you would like to learn more about Deep Learning with practical coding examples, please subscribe to the Murat Karakaya Akademi YouTube Channel or follow


In this post, I will share the Answers to the Questions & Comments about Machine Learning & Deep Learning topics that are posted to my YouTube channel Murat Karakaya Akademi.

If you have any questions please do not hesitate to post them on the Murat Karakaya Akademi YouTube channel. I will reply to them as soon as possible.

You can access many tutorials on Machine Learning & Deep Learning topics implemented by Python, TensorFlow, and Keras in English or Turkish on my YouTube channel Murat Karakaya Akademi.

Last updated: 23 July 2021

Photo by Akhilesh Sharma on Unsplash

Hi, in the tutorial “SEQUENCE-TO-SEQUENCE LEARNING PART F Encoder Decoder with Bahdanau & Luong Attention” (https://youtu.be/FEVCmJXc7eI), if inputs to model is not multiple of batch_size I am getting shape error while training. How can this problem be solved? I have used STEPS_PER_EPOCHS, but still this did not helped

Youı can use “drop_remainder” argument in the tf.data.Dataset…


Makine Öğrenmesi, Derin Öğrenme ve Yapay Zeka konularında; Murat Karakaya Akademi YouTube kanalıma gelen sorular ile yorumları ve onlara verdiğim cevapları aşağıda paylaşıyorum. Umarım benzer soruları olanlara yardımcı olabilirim.

Eğer sizlerin de aklınızdada Makine Öğrenmesi, Derin Öğrenme ve Yapay Zeka konularında sorular varsa, lütfen Murat Karakaya Akademi YouTube kanalıma yazın. Ayrıca isterseniz her ay yaptığım “Soru-Cevap” canlı yayınlarıma katılıp sorunuzu canlı canlı sorabilirsiniz.

Aşağıdaki kayıtlar bu canlı yayınlardır. Sizleri de bir sonraki canlı yayına beklerim. Eğer Murat Karakaya Akademi YouTube kanalıma abone olursanız ve bildirimleri aktif hale getirseniz canlı yayınlardan kolayca haberdar olabilirsiniz.

Canlı yayınlarda görüşmek üzere!

En son güncelleme…


This tutorial is the sixth part of the “Text Generation in Deep Learning with Tensorflow & Keras” series.

In this series, we have been covering all the topics related to Text Generation with sample implementations in Python, Tensorflow & Keras.

In this tutorial, we will focus on how to build a Language Model using the Encoder-Decoder approach with the Bahdanau Attention mechanism for Character Level Text Generation.

Last updated on 25th March 2021.

Photo by Emile Perron on Unsplash

First, we will download a sample corpus (text file).

After opening the file, we will apply the TensorFlow input pipeline that we have developed in Part B

Murat Karakaya

Assoc. Prof. Computer Engineering An enthusiasts of Deep Learning who likes to share the knowledge in a simple & clear manner via coding the solutions.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store