Notebook Master for Jupyter vs LearnML

We believe the best way to learn AI/Deep Learning/Machine learning and Data Science is to enable them to access the reproducible codes on Jupyter. Notebook lets you explore million notebooks on Github/Kaggle and more. * Wonder how to implement new state of the art papers? * How to win a Data Science competition * How to start learning Deep Learning and Machine Learning. You can explore, search, store offline to read and learn your favorite notebooks any time, everywhere, on the go. Thanks to your feedback, we add new ad free subscription version by month/year. ** Functions ** - Open with colab from github - Explore top Jupyter notebook repositories - Search the repositories, users - Import your notebooks from cloud - View and bookmark your most valuable notebooks. - Offline view mode - Beautiful rendering maths in notebook. ** Ad free subscription ** • Length of subscription: monthly/yearly • Payment will be charged to iTunes Account at confirmation of purchase • Subscription automatically renews unless auto-renew is turned off at least 24-hours before the end of the current period • Account will be charged for renewal within 24-hours prior to the end of the current period, and identify the cost of the renewal • Subscriptions may be managed by the user and auto-renewal may be turned off by going to the user’s Account Settings after purchase Enjoy notebooks and happy modeling. Contact us: saigonapps@gmail.com Term of Service and Privacy policy: http://appsaigon.com/privacy.html

Learn how a neural network works by building and training one yourself. LearnML takes you through four steps: Data, Model, Train and Try it. START WITH A WORKING EXAMPLE Make your first prediction with a ready-to-use even-or-odd model. Short explanations show what each step does and what to try next. LEARN THROUGH THREE GUIDED LESSONS • Classify numbers as even or odd. • Predict a temperature from previous values. • Explore image classification with animal photos. The temperature examples are simulated learning data, not a weather forecast service. BUILD AND EXPERIMENT Choose number, vector or image inputs. Edit examples, select the correct answers and build a model from dense, convolution, pooling, activation and dropout layers. Start with a matching model or change its architecture and training settings. TRAIN ON YOUR DEVICE Watch progress and compare training and test metrics. Stop a run when you need to. Try a new number, set of values or photo after training. Predictions can be wrong: use them to explore what the model learned. KEEP YOUR WORK Experiments, examples, trained models and lesson progress are saved locally between launches. Rename and duplicate experiments, keep successful training runs, or export and import an experiment as a JSON file. Interrupted training can be started again from the restored experiment. MADE FOR IPHONE AND IPAD Follow one step at a time on iPhone. Use the sidebar on iPad and view a lesson's explanation beside its practice area when space allows. English and Russian interfaces are included, with support for larger text and improved accessibility controls. No account or cloud training is required. Choose your own photos or use the built-in examples.