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# Python Deep Learning Projects
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![image1][image-1]
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_Authors: [Rahul Kumar][1] & [Matt Fanli Ramsey][2] & [Abhishek Nagaraja][3]
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Authors: [Rahul Kumar][1] & [Matt Fanli Ramsey][2] & [Abhishek Nagaraja][3]
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## Getting Started
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* Link to Packt Publishing: http://bit.ly/DeepLearningProjects
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* Link to Amazon: https://www.amazon.com/Python-Deep-Learning-Projects-Architectures/dp/1788997093
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### Prerequisites
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This course is for intermediate machine learners like if you've undertaken at least one course in machine learning and have a modest functional proficiency in Python (meaning you can create programs in Python when supported by examples). Many of our readers will be undergraduates at university studying computer science, statistics, mathematics, physics, biology, chemistry, marketing, and business.
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In this course, you will need a Google Cloud free tier account. Note that you won't be charged by creating the account. Instead, you can get `300ドル` credit to spend on Google Cloud Platform for 12 months and access to the Always Free tier to try participating products at no charge. By going through this course, you will probably need to spend at most `50ドル` out of your `300ドル` free credit.
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### Authors
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**Rahul Kumar**
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**Abhishek Nagaraja**
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* LinkedIn : https://www.linkedin.com/in/abhishek-nagaraja-4325aa110/
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### Table of contents
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**SECTION I – [Python deep learning – building the foundation]**
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- [x] Chapter 1 : Building Deep Learning Environment
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- [x] Chapter 2 : Training NN for Prediction using Regression
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**SECTION II – [Python deep learning – NLP]**
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- [x] Chapter 3 : Word representation using word2vec
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- [x] Chapter 4 : Build NLP pipeline for building chatbots
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- [x] Chapter 5 : Sequence-to-sequence models for building chatbots
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- [x] Chapter 6 : Generative Language Model for Content Creation
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- [x] Chapter 7 : Building Speech Recognition with DeepSpeech2
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**SECTION I – [Python deep learning – building the foundation]**
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- Chapter 1 : Building Deep Learning Environment
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- Chapter 2 : Training NN for Prediction using Regression
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---
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**SECTION II – [Python deep learning – NLP]**
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- Chapter 3 : Word representation using word2vec
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- Chapter 4 : Build NLP pipeline for building chatbots
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- Chapter 5 : Sequence-to-sequence models for building chatbots
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- Chapter 6 : Generative Language Model for Content Creation
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- Chapter 7 : Building Speech Recognition with DeepSpeech2
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---
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**SECTION II – [Deep learning – Computer Vision]**
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- [x] Chapter 8 : Handwritten Digits Classification Using ConvNets
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- [x] Chapter 9 : Object Detection using OpenCV and TensorFlow
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- [x] Chapter 10: Building Face Recognition using Facenet
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- [x] Chapter 11: Automated Image Captioning
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- [x] Chapter 12: Pose Estimation on 3D models using ConvNets
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- [x] Chapter 13: Image translation using GANs for style transfer
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- Chapter 8 : Handwritten Digits Classification Using ConvNets
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- Chapter 9 : Object Detection using OpenCV and TensorFlow
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- Chapter 10: Building Face Recognition using Facenet
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- Chapter 11: Automated Image Captioning
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- Chapter 12: Pose Estimation on 3D models using ConvNets
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- Chapter 13: Image translation using GANs for style transfer
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---
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**SECTION IV – [Python deep learning – Reinforcement Learning]**
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- [x] Chapter 14: Develop an Autonomous Agents with Deep R Learning
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- [x] Chapter 15: Summary And Next Steps In Your Deep Learning Career
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- Chapter 14: Develop an Autonomous Agents with Deep R Learning
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- Chapter 15: Summary And Next Steps In Your Deep Learning Career
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#### Feel Free to contact us if you have any question:

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