regularization

An Intelligent Autopilot System that Learns Drive

An Intelligent Autopilot System that Learns Drive – AI Project

November 19, 2020May 19, 2021 Sunil Ghimire 4 Comments a driverless-car, An Intelligent Autopilot System that Learns Drive, An Intelligent Autopilot System that Learns Drive - AI Project, Anaconda, automation, CNN, Computer Vision, convnets, Convolution Neural Network, Deep Learning, Dropout, End to End Learning for Self-driving Cars from NVIDIA, GPS, High Level System Architecture, human driver, Intelligent, Intelligent Autopilot System, Intelligent System, Keras, Keras (Tensorflow Backend), laser light, Machine Learning, odometry, Opencv, Python, radar, regularization, robotic-car, self-driving car, Sensory information, Udacity Self driving car, Udacity Self-driving car, Unity

For the past decade, self-driving algorithms have drawn growing research efforts from both industry and academia using low-cost vehicle-mounted cameras.

50 Questions on statistics and machine learning - Can you answer?

Article Interview Questions Latest

50 Questions on Statistics & Machine Learning – Can you answer?

October 31, 2020March 10, 2021 Sunil Ghimire 0 Comments Accuracy, Algorithm, Algorithms, Artificial Intelligence, bias-variance trade-off, binary classification, Cancer Detection, Classification Problem, confusion matrix, continuous variables, convex hull, correlation, Cost, covariance, cross-validation, Data Analysis, Data Science, Data set, Deep Learning, dimension of data, F1-Score:, False alarm rate, Google, Gradient Descent, high variance, Interview Questions, Kmeans clustering, KNN, Lasso regression, likelihood, low bias, Machine Learning, marginal probability, Missing Values, Naive Bayes, PCA, Precision, prior probability, Python, random forest model, Recall, regularization, Ridge regression, Specificity, Statistics, SVM, TIme Series, tree algorithm

We have tried to summarize detailed 50 tricky and insightful questions on statistics and machine learning discussion that should benefit you.