Deep learning specialization github notes View on GitHub Course 1: Neural Networks and Deep Learning. Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow Build Things about the DL specialization from Coursera. Move to Note. ai, on coursera. ai team. I completed the specialization in July 2019 and my review of the series can be found here. Setup Run setup. It is that we want to use this learning problem to learning good word embeddings. Courses Outline Course 1: Neural Networks and Deep Learning May 14, 2024 路 Personal dump of the notes/assignments for all five courses in the Deep Learning Specialization. Deep learning Specialization Notes in One pdf : Reading Deep Learning Specialization Notes. Check my 100 Days of Code Repository here. These notes cover various topics essential for understanding and applying deep learning techniques. Week 1 - Intro to Deep Learning. **Each of the below Courses Contains Notes, programming assignments, and quizzes. Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today. The two main object classes in tensorflow are Tensors and Operators. - GitHub - ppant/deeplearning. md since some formula images are not rendered 馃槩 Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. It's a treasure given by deeplearning. AI and Stanford Online in Coursera, Made by Arjunan K Coursera (Deep_Learning_Specialization) By Andrew Ng and offered by deeplearning. In this Specialization, you will build and train neural network For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. - TianhooZhang/Deep-Learning-Specialization In the third course of the Machine Learning Specialization, you will: Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - randonmess/Deep-Learning-Specialization-Coursera For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. ai-notes: These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. Notes for Deep Learning Specialization Courses led by Andrew Ng. Deep learning Specialization Notes in One pdf : Reading This course is almost the simplest deep learning course I have ever taken, but the simplicity is based on the fabulous course content and structure. Deep learning Specialization Notes in One pdf : Reading Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning Specialization offered by deeplearning. Currently, this repo has 3 major parts you may be interested in and I will give a list here. - iheb2/Deep-Learning-Specialization-Coursera- Welcome to the DeepLearning. Learn to set up a machine learning problem with a neural network mindset. ai - gmortuza/Deep-Learning-Specialization The first course in the Deep Learning Specialization focuses on the foundational concepts of neural networks and deep learning. Convolutional Neural Networks/week 2/Notes/Lecture. Code, quizzes, and notes from the DeepLearning. 7, Apple Pencil and Notability app to write notes The first course in the Deep Learning Specialization focuses on the foundational concepts of neural networks and deep learning. sh to (i) download a pre-trained VGG-19 dataset and (ii) extract the zip'd pre-trained models and datasets that are needed for all the assignments. But the goal of setting up this supervised learning problem isn’t to do well on the supervised learning problem per se. Note: Coursera Honor Code advise against plagiarism. pdf at master · gmortuza/Deep-Learning-Specialization This repository contains the programming assignments and slides from the deep learning course from coursera offered by deeplearning. AI and Coursera. What is a neural network; Supervised learning with neural networks; Why is deep Automate any workflow Packages Contents and notes from specialization in DeepLearning from DeepLearning. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - coursera-deep-learning For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. Caffe/Caffe2; CNTK; DL4J; Keras; Lasagne; mxnet; PaddlePaddle; TensorFlow; Theano; Torch; Choosing deep learning frameworks: Ease of programming (development and deployment) Running speed; Truly open (open source with good governance) Tensorflow. ai . Learn to use vectorization to speed up Oct 18, 2020 路 馃馃懆馃捇Deep Learning Specialization • Lecture Notes • Lab Assignments - GitHub - Rustam-Z/deep-learning-notes: 馃馃懆馃捇Deep Learning Specialization • Lecture Notes • Lab Assignments Course notes, quizzes, and programming assignments for DeepLearning. Model details: About This Specialization (From the official Deep Learning Specialization page) If you want to break into AI, this Specialization will help you do so. 1- Neural Networks and Deep Learning;2- Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization; 3- Structuring Machine Learning Projects; 4- Convolutional Neural Networks;5- Sequence Models. - lakieungocthang/Deep-L This project is a study note on deeplearning. - zhwang0/Coursera-Deep-Learning-Specialization Saved searches Use saved searches to filter your results more quickly Deep Learning Specialization - Projects- Notes. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Week 1: Introduction to Deep Learning Learning Objectives. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - coursera-deep-learning You signed in with another tab or window. 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 For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc. Python Basics with Numpy; Logistic Regression with a Neural Network Mindset; Week 3 - Shallow Neural Networks. You signed out in another tab or window. This repo mainly provides the following features: The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning. 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 This repository contains the programming assignments and slides from the deep learning course from coursera offered by deeplearning. Natural language processing is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language. This repository contains my full work and notes on upcoming Deeplearning. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning Specialization offered by deeplearning. Aug 6, 2024 路 A repository to document and track my progress through the Deep Learning Specialization course by DeepLearning. 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 In the first course of the Deep Learning Specialization, we will study the foundational concept of neural networks and deep learning. AI Deep Learning Specialization by Andrew Ng repository! This repository contains all my coursework, assignments, and projects completed during the Deep Learning Specialization offered by DeepLearning. Contribute to kb1907/Deep-Learning-Specialization development by creating an account on GitHub. The two courses are: This Repo contains all Notes written by me during my classes on Deep Learning Specialization by Andrew NG. Its includes solutions to the quizzes and programming assignments which are required for successful completion of the courses. AI and Stanford Online. Notes, assignments and quizzes from the Coursera Deep Learning specialization offered by deeplearning. This is the first course of the deep learning specialization at Coursera which is moderated by DeepLearning. Learn about the key technology trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep Lecture notes of Deep Learning by Andrew Ng, Deeplearning. Week 1: Introduction to Deep Learning. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - BarakaKim/Notes_Deep Deep learning frameworks. AI, including my own solutions to the practice problems and personal notes accumulated during the course. Complete and detailed pdf plus handwritten notes of Machine Learning Specialization 2022 by Andrew Ng in collaboration between DeepLearning. - Deep-Learning-Specialization/Coursera Deep Learning course Notes. pdf at master · gmortuza/Deep-Learning-Specialization Notes for the Coursera course on Deep Learning. View on GitHub Deep Learning Specialization Course Notes. ai with the marvelous Andrew Ng. ), and when they should be applied; Assess appropriate use cases for deep learning; Introduction to Deep Learning All important notes on deep learning topic, taken from the 5 courses of the Deep Learning Specialization (Coursera) - nhntran/Deep-Learning-Methodology Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. The courses are taught by Andrew Ng and cover both the theory and practical aspects of deep learning. Table of Contents This is not a very easy learning problem, because within ±10 words of the word orange, it could be a lot of different words. Learning Objectives; Introduction to Deep Learning. Course 1: Neural Networks and Deep Learning. Deep Learning is one of the most highly sought after skills in tech. - VrajMalvi/DeepLearning. Building your Deep Neural Network: Step by Step For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. - abbasmzs/Coursera-Deep-Learning-Specialization Deep Learning Specialization course material (e. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - coursera-deep-learning This repository comprises a comprehensive collection of materials for the course of Deep Learning Specialization, offered by Coursera and DeepLearning. AI on Coursera, taught by Andrew Ng. ai. I used iPad Pro 9. Introduction from the specialization page: 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. - ardakdemir/deep-learning-specialization Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Learn about the key technology trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep File / folder Description; 01_neural_networks_and_deep_learning: This folder contains the source code as well as lecture notes for the "Neural Networks and Deep Learning" course. Notes from all courses within the Coursera Deep Learning specialization offered by Andrew NG. - asmitapaul/Notes_coursera-deep-learning-specialization The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. Week 2 - Neural Network Basics. We will help you become good at Deep Learning. The solutions uploaded here are only for reference. This repository contains notes, slides, labs, assignments and projects for the Deep Learning Specialization by DeepLearning. In this Specialization, you will build and train neural network Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Notes of Deep learning courses on Coursera. I have added a multitude of explanations, illustrations, and Week 1: Introduction to deep learning. Contribute to Sroy20/Deep-Learning-Specialization-Notes development by creating an account on GitHub. This is the notes of the Deep Learning Specialization courses offered by deeplearning. This is the notes of the Deep Learning Specialization courses offered by deeplearning. aman. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - AliMahmoudzadeh/coursera About. AI on Coursera. Introduction from the specialization page: In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful I created this repository post completing the Deep Learning Specialization on coursera. Learn about the key technology trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep This is the notes of the Deep Learning Specialization courses offered by deeplearning. ) Coursera deeplearning. Build recommender systems with a collaborative filtering approach and a content-based deep learning method. In every course, I have my notes, my codes, and quizzes (you can solve and submit too!). After years, I decided to prepare and share some notes which highlight key concepts I learned in this specialization. This repository is a placeholder for my notes on Andrew NG's (et al. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Discuss the major trends driving the rise of deep learning; Explain how deep learning is applied to supervised learning; List the major categories of models (CNNs, RNNs, etc. Saved searches Use saved searches to filter your results more quickly This repository contains comprehensive notes from the "Deep Learning Specialization" course. The goal of setting up this repo is to make full use of Dr Andrew Ng's Deep Learning Specialization. Readers are requested to use Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Contains notes, code exercises, and projects. This Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep N Notes by Ricardo Santos. ai - Deep-Learning-Specialization/4. Introduction from the specialization page: In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine A collection of course notes and code snippets for the 5-course Deep Learning specialization on Coursera, developed by deeplearning. Acknowledgement All the programming assignments that are listed are samples of my own work in Coursera Deep Learning specialization offered by deeplearning. AI platform. Learn about the key technology trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Contribute to arpansheetal/Deep-Learning-Specialization development by creating an account on GitHub. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks. I have started this course on 11 th July, 2022. I have used diagrams and code snippets from the code whenever needed but following The Honor Code. Programming assignments and Notes from all courses in the Coursera Deep Learning specialization offered by deeplearning. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - amanchadha/coursera-deep The first course in the Deep Learning Specialization focuses on the foundational concepts of neural networks and deep learning. AI's "Deep Learning Specialization" - haocai1992/Deep-Learning-Specialization If you want to break into AI, this Specialization will help you do so. . Resources Convolutional Neural Networks/week 4/Notes/My_notes. AI-Specialization. This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. , lecture slides, quizzes, programming assignments), updating with my study progress. Contribute to foochane/Deep-Learning-Specialization-Notes development by creating an account on GitHub. The course is taught by Andrew Ng. Reload to refresh your session. Github: YAD2K: Yet Another Darknet 2 Keras. pdf at main · chuksoo/Deep-Learning-Specialization Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. Notes will be sorted according to Course and Week with Topic of the Class as Title. For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. This project provides a step-by-step guide for you easy to follow the Coursera Deep Learning Specialization course. Contribute to freefrog1986/Deep-Learning-Specialization development by creating an account on GitHub. ai, for private study only, not for commercial use. Build a deep reinforcement learning model. ai Assignments and notes related to specialisation. Week 1 - Introduction to Deep Learning: Understand the significant technological trends driving deep learning development and where and how it’s applied. Andrew NG Notes Collection. ai on Coursera. Mar 26, 2023 路 I found this series of courses immensely helpful in my learning journey of deep learning. Contribute to avish2661/DeepLearning-Specialization development by creating an account on GitHub. In this repo each of the five courses has a I recognize the time people spend on building intuition, understanding new concepts and debugging assignments. ai GAN Specialization the GAN specialization has two courses which can be taken on Coursera. Quiz 1: Introduction to deep learning; Week 2: Neural Networks Basics. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural The Deep Learning Specialization provides a comprehensive introduction to deep learning, one of the most transformative technologies in AI. If you want to break into AI, this Specialization will help you do so. g. Andrew NG Machine Learning Notebooks : Reading. This repo contains all the grading programming assignments from courses in Coursera Deep Learning Specialization. Planar Data Classification with One Hidden Layer; Week 4 - Deep Neural Networks. The first course in the Deep Learning Specialization focuses on the foundational concepts of neural networks and deep learning. AI Data Engineering Professional Certificate specialization, showcasing practical projects, skills developed, and a capstone work in data engineering. You switched accounts on another tab or window. Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. The content of these documents is mainly adapted from this GitHub repository. Course 1 - Neural Networks and Deep Learning. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - coursera-deep-learning The first course in the Deep Learning Specialization focuses on the foundational concepts of neural networks and deep learning. They are meant to unblock you if you get stuck somewhere. Learning notes and python code will be included in this repo as well as other helpful references. I am also doing #100 Days of Code, on Day 36 I have started. ai deep learning specialization including all 5 courses: Neural Networks and Deep Learning; Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; Structuring Machine Learning Projects In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. ai - aurimas13/Coursera-Deep-Learning-Specialization Coursera deep learning specialization notes and code [Specialization Page] Notes are taken in the format of QA. ai - pranjal693/Coursera-Deep-Learning-Specialization For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www. ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models - coursera-deep-learning Coursera deep learning specialization notes and code - jguo1002/deep-learning-specialization-coursera. Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization - GitHub - alejo14171/coursera-deep-learning-specialization-spanish-version: Notes, pro Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization - latorc/deep-learning-specialization Sep 18, 2021 路 These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. pwoqd aaiz bcnq omuj ray aqmdej coxs bwmokr mwuulv ulvce