tf.contrib.learn Quickstart  |  TensorFlow



tf.contrib.learn Quickstart  |  TensorFlow

TensorFlow's high-level machine learning API (tf.contrib.learn) makes it easy to configure, train, and evaluate a variety of machine learning models. In this tutorial, you'll use tf.contrib.learn to construct a neural network classifier and train it on the Iris data set to predict flower species based on sepal/petal geometry. You'll write code to perform the following five steps:


Read full article from tf.contrib.learn Quickstart  |  TensorFlow


No comments:

Post a Comment

Labels

Algorithm (219) Lucene (130) LeetCode (97) Database (36) Data Structure (33) text mining (28) Solr (27) java (27) Mathematical Algorithm (26) Difficult Algorithm (25) Logic Thinking (23) Puzzles (23) Bit Algorithms (22) Math (21) List (20) Dynamic Programming (19) Linux (19) Tree (18) Machine Learning (15) EPI (11) Queue (11) Smart Algorithm (11) Operating System (9) Java Basic (8) Recursive Algorithm (8) Stack (8) Eclipse (7) Scala (7) Tika (7) J2EE (6) Monitoring (6) Trie (6) Concurrency (5) Geometry Algorithm (5) Greedy Algorithm (5) Mahout (5) MySQL (5) xpost (5) C (4) Interview (4) Vi (4) regular expression (4) to-do (4) C++ (3) Chrome (3) Divide and Conquer (3) Graph Algorithm (3) Permutation (3) Powershell (3) Random (3) Segment Tree (3) UIMA (3) Union-Find (3) Video (3) Virtualization (3) Windows (3) XML (3) Advanced Data Structure (2) Android (2) Bash (2) Classic Algorithm (2) Debugging (2) Design Pattern (2) Google (2) Hadoop (2) Java Collections (2) Markov Chains (2) Probabilities (2) Shell (2) Site (2) Web Development (2) Workplace (2) angularjs (2) .Net (1) Amazon Interview (1) Android Studio (1) Array (1) Boilerpipe (1) Book Notes (1) ChromeOS (1) Chromebook (1) Codility (1) Desgin (1) Design (1) Divide and Conqure (1) GAE (1) Google Interview (1) Great Stuff (1) Hash (1) High Tech Companies (1) Improving (1) LifeTips (1) Maven (1) Network (1) Performance (1) Programming (1) Resources (1) Sampling (1) Sed (1) Smart Thinking (1) Sort (1) Spark (1) Stanford NLP (1) System Design (1) Trove (1) VIP (1) tools (1)

Popular Posts