# Ai Academy : Deep Learning — Learn DeepLearning Day by Day > Learn DeepLearning Day by Day (iPhone/iPad app by INGOAMPT.) - Source: https://appshunter.io/ios/app/ai-academy-deep-learning/id6740095442 (this page in markdown: same URL + `.md`) - Developer: [INGOAMPT](https://appshunter.io/developer/1704539480) - Category: Education, Books - Price: $2.99 - Age rating: 4+ - Requires: iOS 17 · 24 MB - Languages: American English - Released: 2025-01-09 - Data updated: 2026-08-27 - User reviews in markdown: https://appshunter.io/ios/app/ai-academy-deep-learning/id6740095442/reviews.md ## What is Ai Academy? 80 Days of AI Mastery: Learn Deep Learning Day by Day: Master artificial intelligence and machine learning at your own pace with Day-by-Day Deep Learning—a dynamic and interactive learning app designed to simplify complex topics like neural networks, CNNs, RNNs, Transformers, and more. Whether you’re just starting your AI journey or advancing your deep learning expertise, this app offers everything you need to learn effectively. Key Features: • Interactive Flashcards: Learn with bite-sized flashcards designed for clarity and retention, and mark your progress as you go. • Personalized Notes for Each Topic: Add and save your own notes directly within each topic, making it easy to personalize your learning journey. • Bookmark and Track Progress: Bookmark key topics for quick reference and monitor your overall progress with a detailed dashboard that keeps you motivated. • Mark as Read: Stay organized by marking lessons as read and tracking what’s left to explore. • Offline Access: Learn anytime, anywhere, without needing an internet connection. • Powerful Search Functionality: Quickly find topics or lessons using the robust search tool. • Beginner to Advanced Topics: Cover foundational concepts like supervised learning and neural networks, then dive into advanced topics like NLP, Transformers, and Reinforcement Learning. • Math & Code Support: View beautifully rendered equations and syntax-highlighted code examples for a seamless and professional learning experience. Take your deep learning skills to the next level. Whether you’re learning for work, school, or personal growth, Day-by-Day Deep Learning gives you the tools to succeed. Download now and start your journey to becoming an AI expert today! ## Version history (last 3 releases) ### 2.2 — 2025-02-03 Fixed the material of the content, the material are more up to date for 2025 and all information got better and more up to date :  Now is 80 articles fixed and updated for 2025 to learn ai - deep learning step by step in 80 days : topics covered are : 80 days topics include in this app are : Intro to ML – ML types, models, train-test split. ML in iOS – Using ML in apps. Model Types – Supervised vs. unsupervised. Regression & Classification – Basics with MNIST. SGD Math – How it works. Normal Equation – Prediction without iteration. Gradient Descent – Concept and application. Types of GD – Batch, Stochastic, Mini-Batch. Perceptrons – Deep learning basics. MLPs – Regression vs. classification. Activation Functions – ReLU, Sigmoid, etc. Non-Linearity – Hidden layers & activation. Intro to Keras – Building models. Keras APIs – Sequential, Functional, Subclassing. Keras API Comparison – Sequential vs. Functional. TensorFlow Tools – TensorBoard, callbacks, saving models. Hyperparameter Tuning – With Keras Tuner. Manual vs. Auto Optimization – Tuning models. Bayesian Optimization – Neural network tuning. Vanishing Gradient – Explanation. Weight Initialization – Strategies. Monetizing AI APIs – Creating paid APIs. Weight Init: Part 2 – Advanced methods. Advanced Activation – GELU, Mish, etc. Batch Norm – How it works. Batch Norm: Part 2 – Further details. Batch Norm Parameters – Trainable/non-trainable. Gradient Clipping – Avoid exploding gradients. Transfer Learning – Basics. Transfer Learning Example – Implementing it. Labeled vs. Unlabeled Data – Differences. Speeding Up Training – Optimization tricks. Momentum Optimization – Deep dive. Momentum vs. Normalization – Comparisons. Momentum: Part 3 – Advanced details. NAG Optimizer – Nesterov Accelerated Gradient. AdaGrad – Origins & proof. Optimizer Comparison – AdaGrad, RMSProp, Adam. Adam vs. Other Optimizers – Pros & cons. Adam & Local Minima – Understanding behavior. More Optimizers – NAdam, AdaMax, AdamW. Learning Rate Schedules – Why they matter. 1Cycle Schedule – Explanation. Gradient Clipping & Weight Init – Combined effect. LR Scheduling Methods – 1-Cycle, CED, Exponential. TensorFlow vs. PyTorch vs. MLX – Frameworks compared. Regularization – Preventing overfitting. Dropout – Including MC Dropout. Max-Norm Regularization – Explanation. Deep vs. Dense Networks – Differences. Deep Learning Use Cases – Overview. ML in iOS Apps – Integration. CNNs – Basics & use cases. CNN Math – How it works. RNNs: Part 1 – Sequence modeling. RNNs: Part 2 – More details. RNNs & Time Series – Forecasting. RNN vs. Feedforward – Mathematical comparison. ARIMA & SARIMA – Before diving into RNNs. RNN Step-by-Step – Time series forecasting. Seq2Seq Forecasting – Iterative vs. direct. LSTMs & Layer Norm – RNN enhancements. RNNs for NLP – Language modeling. Why Transformers Win in NLP – Key insights. Transformers Overview – GPT to DeepSeek. Transformer Breakthroughs – ChatGPT to DeepSeek. BERT Explained – Key insights. How ChatGPT Works – Basics. ChatGPT vs. BERT – Understanding comparison. ChatGPT: Step-by-Step – Breakdown. NLP Mathematics – Behind modern AI models. Transformers in Vision & Multimodal AI – Expansion. Autoencoders, GANs, & Diffusion – Overview. Stacked Autoencoders – Unsupervised pretraining. Diffusion Models – Breaking them down. GANs – Deep learning for image generation. How DALL·E Works – Image synthesis. Reinforcement Learning – Applications & impact. DeepNet – Scaling Transformers to 1,000 layers. DeepSeek-R1 – Advancing LLM reasoning. ### 2 — 2025-01-27 Improved Content & Math View Correctio Added A View Full Screen To Read The Article With Full Screen Added Correctly Work On Dark And Light Mode Available from iOS 17 Chang the SubTitle name Topic List AI ACADEMY : DEEP LEARNING Machine Learning (ML) Overview - Day 1 Integrate ML Into iOS Apps - Day 2 Models-Based, Instance Models, Train-Test Splits: The Building Blocks of Machine Learning - Day 3 Regression & Classification With MNIST - Day 4 Mathematical Explanation Behind SGD Algorithm - Day 5 Can We Make Predictions Without Iteration? - Day 6 What Is Gradient Descent? - Day 7 Three Types of Gradient Descent: Batch, Stochastic & Mini-Batch - Day 8 Deep Learning: Perceptrons - Day 9 Regression vs. Classification in MLPs - Day 10 Activation Function - Day 11 Activation Function, Hidden Layer, and Non-Linearity - Day 12 What Is Keras? - Day 13 Sequential, Functional, and Subclassing API in Keras - Day 14 Sequential vs. Functional Keras API: Part 2 - Day 15 TensorFlow: Using TensorBoard and Callbacks - Day 16 Hyperparameter Tuning With Keras Tuner - Day 17 Automatic vs. Manual Optimization in Keras - Day 18 Exploring Bayesian Optimization - Day 19 Vanishing Gradient Explained in Detail - Day 20 Weight Initialization in Deep Learning - Day 21 How to Create an API With Deep Learning - Day 22 Weight Initialization: Part 2 - Day 23 Activation Function Progress: Relu, Elu, Mish, etc. - Day 24 Batch Normalization - Day 25 Batch Normalization: Part 2 - Day 26 Batch Normalization: Trainable vs. Non-Trainable - Day 27 Understanding Gradient Clipping - Day 28 Transfer Learning - Day 29 How to Perform Transfer Learning: Examples - Day 30 Labeled vs. Unlabeled Data in ML - Day 31 Deep Neural Network Optimization Techniques - Day 32 Momentum Optimization Explained - Day 33 Momentum vs. Normalization - Day 34 Momentum: Part 3 - Day 35 NAG as an Optimizer - Day 36 AdaGrad: Origins and Mathematical Proof - Day 37 AdaGrad vs. RMSProp vs. Adam - Day 38 Adam vs. SGD vs. AdaGrad - Day 39 Adam Optimizer: Understanding Local Minimum - Day 40 Optimizers: NAdam, AdaMax, AdamW, etc. - Day 41 Learning Rates and Schedules Explained - Day 42 1-Cycle Scheduling and Learning Rates - Day 43 Gradient Clipping and Weight Initialization - Day 44 Learning Rate: CED and Exponential Decay - Day 45 Comparing TensorFlow, PyTorch, and MLX - Day 46 Understanding Regularization in Deep Learning - Day 47 Dropout and Monte Carlo Dropout - Day 48 Max-Norm Regularization in Deep Learning - Day 49 Deep Neural Networks vs. Dense Networks - Day 50 Deep Learning Examples: Overview - Day 51 Integrating DL Models Into iOS Apps - Day 52 CNN: Convolutional Neural Networks Explained - Day 53 Mathematics Behind CNNs - Day 54 RNN Deep Learning: Part 1 - Day 55 Understanding RNNs: Part 2 - Day 56 Time Series Forecasting With RNNs - Day 57 RNNs vs. FNNs: Understanding the Math - Day 58 Learn RNNs by Understanding ARIMA - Day 59 Step-by-Step RNN Forecasting - Day 60 Iterative and Seq2Seq Models for Forecasting - Day 61 RNN, Layer Normalization, and LSTMs - Day 62 Natural Language Processing and RNNs - Day 63 Why Transformers Are Better for NLP - Day 64 The Transformer Model Revolution - Day 65 Transformers in Deep Learning - Day 66 BERT Explained in 2 Minutes - Day 67 ChatGPT for Clinical and Medical Applications - Day 68 ChatGPT vs. BERT: Comparison - Day 69 How ChatGPT Works Step by Step - Day 70 Mastering NLP With a Scientific Paper Study - Day 71 Transformers in Vision and Multimodal Models - Day 72 Secrets of Autoencoders, GANs, and Diffusion Models - Day 73 Unsupervised Pretraining With Autoencoders - Day 74 Breaking Down Diffusion Models - Day 75 GANs in Deep Learning - Day 75 How DALL·E Image Generator Works - Day 77 ### 1.4 — 2025-01-09 No release notes. ## Apps similar to Ai Academy | App | Rating | Price | Category | | --- | --- | --- | --- | | [Abnormal Translator](https://appshunter.io/ios/app/abnormal-translator/id6757080398) | 5.0 (1) | Free | Education | | [Azure Cloud Prep: with AI](https://appshunter.io/ios/app/azure-cloud-prep-with-ai/id6762596343) | — | Free | Education | | [NabQuiz](https://appshunter.io/ios/app/nabquiz/id6762571924) | — | Free | Education | | [I Learn: Phonics for Kids](https://appshunter.io/ios/app/i-learn-phonics-for-kids/id996078190) | 5.0 (10) | $4.99 | Education | | [Hanzi Easy: Grow Chinese Vocab](https://appshunter.io/ios/app/hanzi-easy-grow-chinese-vocab/id6758232186) | — | Free | Education | | [Hanzi Stroke: Chinese Write](https://appshunter.io/ios/app/hanzi-stroke-chinese-write/id6763503899) | 3.7 (3) | Free | Education | ## More apps by INGOAMPT - 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User reviews are verbatim App Store reviews. Ratings, prices and chart positions refresh continuously; this snapshot is from 2026-08-27.*