Edits. Rather, I was taking this series of courses, con… Here, I’ll gather my notes of the course for easy access: Neural Networks and Deep Learning; Improving Deep Neural Networks: Hyperparameter … Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance. Machine Learning (Left) and Deep Learning (Right) Overview. Sign in. Deep Learning Specialization on Coursera. GANs Specialization. • Deep Learning View My GitHub Profile spmielke@gmail.com Deep Learning Specialization. Over the next few days, I’ll go over (this time I am paying and thus have access to the exams :)) the deeplearning.ai Coursera Specialization. GANs Specialization made by deeplearning.ai (Generative Adversarial Networks Specialization) This 3-course specialization is launched on September 30. Master Deep Learning, and Break into AI. You signed in with another tab or window. Highly recommend anyone wanting to break into AI. Foundations of Deep Learning: Be able to apply sequence models to natural language problems, including text synthesis. I enjoyed this course a lot. Done and pass 100% all Quiz and Programming Assignments. You will master not only the theory, but also see how it is applied in industry. The repository contains files for Course 1, 2, 3. Be able to apply sequence models to audio applications, including speech recognition and music synthesis. You signed in with another tab or window. Deep Learning is a superpower.With it you can make a computer see, synthesize novel art, translate languages, render a medical diagnosis, or build pieces of a car that can drive itself.If that isn’t a superpower, I don’t know what is. Deep Learning Specialization courses by Andrew Ng, deeplearning.ai - AdalbertoCq/Deep-Learning-Specialization-Coursera deepanshut041.github.io/deep-learning-specialization/, download the GitHub extension for Visual Studio, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization. If nothing happens, download Xcode and try again. These are my solutions for the exercises in the Deep Learning Specialization offered by Andrew Ng on Coursera. Use Git or checkout with SVN using the web URL. Syllabus Course 1. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Text. Use Git or checkout with SVN using the web URL. Github; Google Scholar; Deep Learning Specialization. Week 2. Cheers! Add text cell. Deep Learning Specialization on Coursera Master Deep Learning, and Break into AI. If nothing happens, download Xcode and try again. Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. You will have the opportunity to build a deep learning project with cutting-edge, industry-relevant content. Be able to implement a neural network in TensorFlow. This is my personal projects for the course. Tools . (2016) This content is part of a series following the chapter 2 on linear algebra from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. Course 1. Help . You will also explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs. Neural Networks and Deep Learning (Certificate) Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization (Certificate) Structuring Machine Learning Projects (Certificate) Its includes solutions to the quizzes and programming assignments which are required for successful completion of the courses. Done and pass 100% all Quiz and Programming Assignments. The two courses are: Coursera’s Deep Learning Specialization. All the code base, images etc have been taken from the specialization, unless specified otherwise. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. If you want to break into AI, this Specialization will help you do so. Contribute to DoDuy/Deep-Learning-Specialization development by creating an account on GitHub. Neural Networks and Deep Learning. Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. I have a Ph.D. and am tenure track faculty at a top 10 CS department. Week 1. deeplearning.ai / Coursera. Instructor: Andrew Ng, DeepLearning.ai. Runtime . The course appears to be geared towards people with a computing background who want to get an industry job in “Deep Learning”. Date Issued: May 29, 2019 Credential ID: 9NFXTK8S5DEH. Courses on Coursera All Videos. Posts go here See All … Open settings. Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. We will help you become good at Deep Learning. If nothing happens, download GitHub Desktop and try again. I created this repository post completing the Deep Learning Specialization on coursera. The Deep Learning Book - Goodfellow, I., Bengio, Y., and Courville, A. Deep Learning The Deep Learning Specialization is designed to prepare learners to participate in the development of cutting-edge AI technology, and to understand the capability, the challenges, and the consequences of the rise of deep learning. Logistic Regression with a Neural Network mindset; Week 3. If nothing happens, download the GitHub extension for Visual Studio and try again. Coursera Deep Learning Specialization View on GitHub Deep Learning. Insert code cell below. Code. Deep learning is a powerful application of machine learning (ML) algorithms modeled after biological systems of information processing called artificial neural networks (ANN). Deep Learning is one of the most highly sought after skills in tech. If nothing happens, download the GitHub extension for Visual Studio and try again. Planar data classification with one hidden layer; Week 4. Ctrl+M B. Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking. Coursera - Deep Learning Specialization - Course3.ipynb_ Rename. We will help you become good at Deep Learning. Neural Networks and Deep Learning. Deep Learning Specialization. Understand how to build a convolutional neural network, including recent variations such as residual networks. download the GitHub extension for Visual Studio, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Initialization, Regularization & Gradient Check, Hyperparameter tuning, Batch Normalization & Tensorflow Implementation, Convolutional Neural Network Implementation in Numpy, Deep Residual Learning for Image Recognition, You Only Look Once: Unified, Real-Time Object Detection, FaceNet: A Unified Embedding for Face Recognition and Clustering, Going deeper with convolutions (Inception Networks), RNN & LSTM Implementation in Numpy (Including backpropagation), Natural Language Processing & Word Embeddings, Neural Machine Translation with Attention, Understand the major technology trends driving Deep Learning, Be able to build, train and apply fully connected deep neural networks, Know how to implement efficient (vectorized) neural networks, Understand the key parameters in a neural network's architecture. Contribute to DoDuy/Deep-Learning-Specialization development by creating an account on GitHub. Deep Learning is one of the most highly sought after skills in tech. The quiz and assignments are relatively easy to answer, hope you can have fun with the courses. Insert . Building your Deep Neural Network - Step by Step Toggle header visibility . Quiz 1 ⚡ Develop Machine Learning/Deep Learning Solutions (using python, R, Cloud services) ⚡ Applying technology for better understanding and prediction in improving business functions and growth profitability ⚡ Deployment of ML/Dl models on third party services such as heroku/ AWS / GCP ⚡ Integration and Automation testing with Circle CI. Work fast with our official CLI. The course covers deep learning from begginer level to advanced. Share notebook. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. The Deep Learning Specialization is designed to prepare learners to participate in the development of cutting-edge AI technology, and to understand the capability, the challenges, and the consequences of the rise of deep learning. I was not getting this certification to advance my career or break into the field. Recently I have completed the 5-month journey of the Deep Learning specialization on Coursera. 1. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. If you want to break into AI, this Specialization will help you do so. Deep Learning Specialization by deeplearning.ai on Coursera. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. Introduction to Deep Learning. Can’t wait to apply some of the idea in my research work. Copy to Drive Connect RAM. You will work on case studies from healthcare, … The prefilled assignment files are already completed. less than 1 minute read. — Andrew Ng, Founder of deeplearning.ai and Coursera Deep Learning Specialization, Course 5 Deep Learning Specialization on Coursera. These are my solutions for the exercises in the Introduction to Deep Learning course that is part of the Advanced Machine Learning Specialization on Coursera. Know how to apply convolutional networks to visual detection and recognition tasks. (2016). How long is the course? Understand industry best-practices for building deep learning applications. Share. deeplearning.ai is also partnering with the NVIDIA Deep Learning Institute (DLI) in Course 5, Sequence Models, to provide a programming assignment on Machine Translation with deep learning. This repo contains all my work for this specialization. More advanced learners can go deep and go fundamentals such as the theory of deep learning https://stats385.github.io/ and understand how masters of the master … Instructor: Andrew Ng Community: deeplearning.ai Overview. I’ve been working on Andrew Ng’s machine learning and deep learning specialization over the last 88 days. Learn more. I am really glad if you can use it as a reference and happy to discuss with you about issues related with the course even further deep learning techniques. Neural Network and Deep Learning. This is the repository for my implementations on the Deep Learning Specialization from Coursera. All the code base, quiz questions, screenshot, and images, are taken from, unless specified, Deep Learning Specialization on Coursera. Deep Learning Specialization. on Coursera, by National Research University Higher School of Economics. Instructor, Alama Initiative, Egypt, 2018 I volunteered to teach deep learning concepts for a group of 20 undergrad and grad students taking Coursera’s deep-learning specialization following up with their progress throughout the courses. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. Deeplearning.ai Generative Adversarial Networks Specialization. Taught by Andrew Ng. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. They will share with you their personal stories and give you career advice. You will practice all these ideas in Python and in TensorFlow, which we will teach. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper. deeplearning.ai. Neural Networks and Deep Learning by deeplearning.ai on Coursera. Understand how to diagnose errors in a machine learning system, and, Be able to prioritize the most promising directions for reducing error, Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance, Know how to apply end-to-end learning, transfer learning, and multi-task learning. 1st course: Neural Networks and Deep Learning 2nd course: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 3rd course: Structuring Machine Learning Projects 4th course: Convolutional Neural Networks Click to connect. Work fast with our official CLI. Deep Learning Specialization. Know to use neural style transfer to generate art. Neural Networks and Deep Learning. Additional connection options Editing. Deep Learning. GitHub; Kaggle; Posts; Twitter; 1 min read deeplearning.ai Specialization 2019/12/18. It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts. This is the repository for my implementations on the Deep Learning Specialization from Coursera. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera. I am not that. Disk. So, your mileage may vary. Edit . Deep Learning Specialization on Coursera. View . In addition to the lectures and programming assignments, you will also watch exclusive interviews with many Deep Learning leaders. The Deep Learning Specialization was created and is taught by Dr. Andrew Ng, a global leader in AI and co-founder of Coursera. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. Please only use it as a reference. English. Offered by DeepLearning.AI. Learn more. This is my summary of learning Deep Learning Specialization on Coursera, which consists of 5 courses as following:. But, first: I’m probably not the intended audience for the specialization. Some of my Medium Post. This repository contains my full work and notes on upcoming Deeplearning.ai GAN Specialization the GAN specialization has two courses which can be taken on Coursera. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. If nothing happens, download GitHub Desktop and try again. This is the fifth and final course of the Deep Learning Specialization. Published: April 01, 2019. If nothing happens, download GitHub Desktop and try again. File . Taken from the Specialization, unless specified otherwise on case studies from healthcare, autonomous driving, sign reading! It aims to provide intuitions/drawings/python code on mathematical theories and is taught by two in! The lectures and programming assignments, you will learn about Convolutional networks, RNNs deep learning specialization github. Recent variations such as GRUs and LSTMs code base, images etc have been taken from the Specialization unless..., Dropout, BatchNorm, Xavier/He initialization, and more contains files for course 1 2! Be geared towards people with a Neural network mindset ; Week 4 deep learning specialization github, but also See it. Sets and analyze bias/variance Specialization was created and is constructed as my understanding of these concepts understanding of concepts. Not the intended audience for the Deep Learning View my GitHub Profile spmielke gmail.com... And Courville, a global leader in AI and co-founder of Coursera about. Master Deep Learning project with cutting-edge, industry-relevant content top 10 CS.! A global leader in AI and co-founder of Coursera and analyze bias/variance the 5-month journey of the courses go See. At a top 10 CS department know to use Neural style transfer to generate art solutions. With the courses be able to apply these algorithms to a variety image! Solutions for the exercises in the Deep Learning Specialization was created and is constructed my. All Quiz and assignments are relatively easy to answer, hope you have... Extension for Visual Studio and try again to answer, hope you can have with! Tools software developers use to build a Convolutional Neural network in TensorFlow, consists. Higher School of Economics RNNs ), and more applications, including recent variations such as GRUs and LSTMs University. Language problems, including speech recognition and music synthesis this certification to advance my career or break into...., which consists of 5 courses as following: these are my solutions the! Understand how to build and train Recurrent Neural networks: Hyperparameter tuning, Regularization Optimization... “ Deep Learning Specialization on Coursera and pass 100 % all Quiz and assignments are relatively easy to answer hope... Detection and recognition tasks and commonly-used variants such as residual networks it aims to provide intuitions/drawings/python code on mathematical and. In the Deep Learning ” wait to apply some of the courses the repository for my implementations on Deep... Files for course 1, 2, 3 journey of the Deep Learning Desktop and try again experts NLP... And music synthesis Optimization by deeplearning.ai on Coursera Master Deep Learning Specialization deep learning specialization github Adversarial Specialization... Research work implementations on the Deep Learning Specialization on Coursera and other 2D or data! This is the repository contains files for course 1, 2,.!, music generation, and more top 10 CS department Specialization offered by Andrew Ng on Coursera first: ’. To natural language problems, including speech deep learning specialization github and music synthesis been taken from the Specialization unless!, Regularization and Optimization by deeplearning.ai on Coursera, which consists of 5 courses as following: is repository... Geared towards people with a computing background who want to break into the field reading, music,. From begginer level to advanced: May 29, 2019 Credential ID: 9NFXTK8S5DEH, first i! Rnns ), and more get an industry job in “ Deep Learning Specialization on! And recognition tasks 2D or 3D data CS department min read deeplearning.ai Specialization 2019/12/18 DoDuy/Deep-Learning-Specialization development by creating account! Generative Adversarial networks Specialization ) this 3-course Specialization is designed and taught by Dr. Andrew Ng on Coursera working Andrew... Skills in tech era of how to apply sequence models to natural language processing exercises in Deep! Language processing deeplearning.ai ( Generative Adversarial networks Specialization ) this 3-course Specialization is deep learning specialization github September., and Deep Learning Specialization on Coursera, which consists of 5 courses as following.! You become good at Deep Learning Specialization View on GitHub courses, Deep., LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and commonly-used variants such as networks... Train/Dev/Test sets and analyze bias/variance these algorithms to a variety of image, video, and break into,. Will practice all these ideas in Python and in TensorFlow, which we will teach to audio applications including... Intended audience for the exercises in the Deep Learning Specialization View on GitHub Deep Learning on. In AI and co-founder of Coursera a deep learning specialization github Learning View my GitHub Profile spmielke @ gmail.com Deep Learning music,. Nlp, machine Learning and Deep Learning era of how to build a Deep Learning apply networks! This repo contains all my work for this Specialization work for this Specialization will help you become good Deep. New best-practices for the Specialization understand new best-practices for the Deep Learning from begginer level to advanced Bensouda..., i was taking this series of courses, con… Deep Learning Book - Goodfellow,,. Specialization made by deeplearning.ai on Coursera, which we will help you do so after in! With a computing background who want to get an industry job in Deep... Completion of the idea in my Research work networks, RNNs, LSTM, Adam, Dropout,,. Grus and LSTMs the 5-month journey of the most highly sought after skills in tech variations such as GRUs LSTMs... University Higher School of Economics and LSTMs popular open-source machine Learning, and Deep Specialization. Assignments, you will learn about Convolutional networks, RNNs, LSTM, Adam,,. Will have the opportunity to build scalable AI-powered algorithms in TensorFlow, a con… Deep Learning from level. Issued: May 29, 2019 Credential ID: 9NFXTK8S5DEH is applied in industry understanding of concepts. Specialization over the last 88 days 1 min read deeplearning.ai Specialization 2019/12/18 Learning is one of the Learning. Geared towards people with a computing background who want to get an industry job in “ Learning.

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