Explain with an example how He_normal initializer work?
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

Explain with an example how He_normal initializer work?

Explain with an example how He_normal initializer work?

This recipe explains with an example how He_normal initializer work

Recipe Objective

He_Normal initializer

He_Normal initializer takes samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / fan_in) where fan_in is the number of input units in the weight tensor.

Step 1- Importing Libraries

import numpy as np import keras from keras.models import Sequential from keras.layers import Activation, Dense import tensorflow as tf

Step-2 Initializing the He_normal initializers.

We show you two ways to initialize the He_normal initializers.

initializer = tf.keras.initializers.HeNormal() values = initializer(shape=(2, 2)) layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)

Step 3- We will create the model

We will be reshaping and creating the model

# define input data X = np.array([17, 35, 400, 230]) # show input data for context print(X) # reshape input data into one sample a sample with a channel X = X.reshape((1, 2, 2, 1)) # define model model = Sequential() model.add(Dense(13, input_dim=13, kernel_initializer=initializer, activation='relu')) model.summary()

Relevant Projects

Predict Employee Computer Access Needs in Python
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

Digit Recognition using CNN for MNIST Dataset in Python
In this deep learning project, you will build a convolutional neural network using MNIST dataset for handwritten digit recognition.

Predict Macro Economic Trends using Kaggle Financial Dataset
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.

Image Segmentation using Mask R-CNN with Tensorflow
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.

Churn Prediction in Telecom using Machine Learning in R
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.

Census Income Data Set Project - Predict Adult Census Income
Use the Adult Income dataset to predict whether income exceeds 50K yr based on census data.

Machine Learning Project to Forecast Rossmann Store Sales
In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.

Loan Eligibility Prediction using Gradient Boosting Classifier
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

House Price Prediction Project using Machine Learning
Use the Zillow dataset to follow a test-driven approach and build a regression machine learning model to predict the price of the house based on other variables.