[unable to retrieve full-text content]Gradient Boosting in TensorFlow vs XGBoost; Managing Machine Learning Workflows with Scikit-learn Pipelines Part 2; Using Genetic Algorithm for Optimizing Recurrent Neural Networks; The Value of Semi-Supervised Machine Learning; Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI
Original Post: KDnuggets™ News 18:n04, Jan 24: TensorFlow vs XGBoost; Machine Learning Pipelines in Python; Semi-Supervised Machine Learning
[unable to retrieve full-text content]For many Kaggle-style data mining problems, XGBoost has been the go-to solution since its release in 2016. It’s probably as close to an out-of-the-box machine learning algorithm as you can get today.
Original Post: Gradient Boosting in TensorFlow vs XGBoost
[unable to retrieve full-text content]Also Japanese scientists just used #AI #DeepLearning to read minds and it’s amazing; Using #DeepLearning to Solve Real World Problems.
Original Post: Top KDnuggets tweets, Jan 10-16: The Art of Learning #DataScience; Gradient Boosting in #TensorFlow vs XGBoost
[unable to retrieve full-text content]This is the narrative of a typical AI Sunday, where I decided to look at building a sequence to sequence (seq2seq) model based chatbot using some already available sample code and data from the Cornell movie database.
Original Post: A Day in the Life of an AI Developer
[unable to retrieve full-text content]How to customize the optimizers to speed-up and improve the process of finding a (local) minimum of the loss function using TensorFlow.
Original Post: Custom Optimizer in TensorFlow
[unable to retrieve full-text content]Also #TensorFlow: A proposal of good practices for files, folders and models; Creating REST API for #TensorFlow models; The Most Popular Language For #MachineLearning and #DataScience Is …
Original Post: Top KDnuggets tweets, Dec 27 – Jan 02: 10 Free Must-Read Books for #MachineLearning and #DataScience
[unable to retrieve full-text content]So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.
Original Post: Deep Learning Made Easy with Deep Cognition
[unable to retrieve full-text content]The Art of Learning #DataScience; How to Generate FiveThirtyEight Graphs in #Python; #TensorFlow for Short-Term Stocks Prediction; 15 Mathematics MOOCs for #DataScience.
Original Post: Top KDnuggets tweets, Dec 13-19: The Art of Learning Data Science; Data Science, ML Main Developments, Key Trends