Neural Network vs Data Structure Display Uso e estatísticas

Learning and using neural networks in an intuitive and natural way! Intuitive and interactive tutorials. A large number of charts and interactive components are used to make learning more intuitive. Visualized Neural Network Lab. Open the black box of neural networks with simplified datasets and full visualization, gain more intuition. Learning with mission like gaming. In the missions, you will run into many key concepts in neural networks, complete the challenges and acquire a deep understanding. Put neural network lab in your pocket. Variety of datasets: 2D and 3D datasets both with regression and classification. Get the dataset just with a tapping. Do experiments at anytime anywhere. Good visualized neural network knowledges. Key concepts and dynamics are showed with charts and animations. Activations, regularizations, loss functions, classifications, Embedding, CNN1d, CNN2d, RNN and more to come. Visualized Deep Learning Models. Learn the most classic models in an intuitive way that has never been seen before, and quickly master cutting-edge technology. Through modular diagrams, understand how data changes from input to output and how it changes at each step. There are detailed documents for each module, and even reference papers, source codes and animations. Visual neural network model editor. Quickly build a model by dragging your fingers. What you see is what you get: Through real-time calculation and display of the output of each step, the construction of the model has never been so intuitive and efficient; real-time display of various errors, including parameters/input types and value compatibility, etc., abandoning inefficient debugging. MORE FEATURES COMING!!!
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A novel data structure learning app, the most significant feature is that you can dynamically debug the data structure in this app, and visually observe the changes in the data structure during the operation. In this app you can learn the following data structures: 1. Linear structures, including arrays, linked lists, queues, stacks. Linear structures are the basis for other advanced data structures, as fine as advanced algorithms. 2. Tree structures, including binary tree, binary search tree, AVL tree, red-black tree, and heap. In this app, you can dynamically debug three traversals of the binary tree (including non-recursive traversal implementations), searching in the tree, balance adjustments in the AVL tree and red-black tree, and heap sorting. Give you the ability of handwritten red-black trees. 3. Graph structure, including the adjacency list storage representation of the graph structure, depth-first search and breadth-first search, finding the Euler path in the graph, topological sorting, maximum connected components, minimum spanning tree problem, and shortest single source Path problem. It also provides dynamic debugging of these classic graph algorithms. 4. The data structure introductory class will talk about the problem of the Tower of Hanoi. The algorithm that solves this problem is often recursive. This app provides dynamic debugging of the Tower of Hanoi problem, so you can no longer be confused about the recursive calls of the Tower of Hanoi.
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Neural Network VS.
Data Structure Display

31ezembro d, 2024