Hits: 2 How to implement K-Nearest Neighbors Algorithm in Python and Scikit-Learn The K-nearest neighbors (KNN) algorithm is a type of supervised machine learning algorithms. KNN is extremely easy to implement in its most basic form, and yet performs quite complex classification tasks. It is a lazy learning algorithm since it doesn’t have a specialized training phase. …
Hits: 5 How to do K-Means Clustering with Scikit-Learn in Python Introduction K-means clustering is one of the most widely used unsupervised machine learning algorithms that forms clusters of data based on the similarity between data instances. For this particular algorithm to work, the number of clusters has to be defined beforehand. The K in …
Hits: 4 Linear Regression using sklearn Linear Regression is a machine learning algorithm based on supervised learning. It performs a regression task. Regression models a target prediction value based on independent variables. It is mostly used for finding out the relationship between variables and forecasting. Different regression models differ based on – the kind …
Hits: 2 Mini-Batch Gradient Descent with Python In machine learning, gradient descent is an optimization technique used for computing the model parameters (coefficients and bias) for algorithms like linear regression, logistic regression, neural networks, etc. In this technique, we repeatedly iterate through the training set and update the model parameters in accordance with the …
Hits: 9 Multiclass classification using scikit-learn Multiclass classification is a popular problem in supervised machine learning. Problem – Given a dataset of m training examples, each of which contains information in the form of various features and a label. Each label corresponds to a class, to which the training example belongs to. In multiclass classification, we have …
Hits: 6 (How to setup Dropout Regularization in Keras) In this Learn through Codes example, How to setup Dropout Regularization in Keras. Dropout_Regularization_on_the_Visible_Layer Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data Analytics as well as Time …
Hits: 60 Data Science Project on President Heights If you are a beginner in Data Science you must solve this project, as you will learn a lot about working on Data, that comes from a csv file or any other formats. This data is available in the file heights.csv, which is a simple comma-separated list …
Hits: 40 (Binary Classification – Smaller Keras Model in Python with Standardized data) In this Learn through Codes example, you will learn Binary Classification – Smaller Keras Model in Python with Standardized data. Binary_Classification_Smaller_Keras_Model_in_Python_with_Standardized_data Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring …
Hits: 43 (Binary Classification with Sonar Dataset: Baseline Keras Model in Python with Standardized data) In this Learn through Codes example, you will learn Binary Classification with Sonar Dataset: Baseline Keras Model in Python with Standardized data. Baseline_Keras_Model_in_Python_with_Standardized_data Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes …
Hits: 22 (Machine Learning algorithm Pipeline in Python using scikit-learn) In this Learn through Codes example, you will learn Machine Learning algorithm Pipeline in Python using scikit-learn. Machine_Learning_algorithm_Pipeline_in_Python_using_scikit_learn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data …
Hits: 17 (Bagging Ensemble Machine Learning algorithms in Python using scikit-learn) In this Learn through Codes example, you will learn Bagging Ensemble Machine Learning algorithms in Python using scikit-learn. Bagging_Ensemble_Machine_Learning_algorithms_in_Python_using_scikit_learn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text …
Hits: 55 (How to compare machine learning algorithms in Python using sklearn) In this Learn through Codes example, you will learn How to compare machine learning algorithms in Python using sklearn. Compare_machine_learning_algorithms_in_Python_using_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular …
Hits: 15 (Keras Deep Learning with Grid Search using sklearn) In this Learn through Codes example, you will learn Keras Deep Learning with Grid Search using sklearn. Keras_Deep_Learning_with_Grid_Search_using_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data …
Hits: 15 (Keras Deep Learning with 10-fold cross validation using sklearn) In this Learn through Codes example, you will learn Keras Deep Learning with 10-fold cross validation using sklearn. Keras_Deep_Learning_with_10-fold_cross_validation_using_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & …
Hits: 17 (Regression Machine Learning Algorithms in Python with scikit-learn) In this Learn through Codes example, you will learn Regression Machine Learning Algorithms in Python with scikit-learn. Regression_Machine_Learning_Algorithms_in_Python_with_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data …
Hits: 8 (Random Search Parameter Tuning in Python using scikit-learn) # import python packages import numpy as np from scipy.stats import uniform as sp_rand from sklearn import datasets from sklearn.linear_model import Ridge from sklearn.model_selection import RandomizedSearchCV # load the diabetes datasets dataset = datasets.load_diabetes() # prepare a uniform distribution to sample for the alpha parameter …