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Pralabh Saxena
Pralabh Saxena

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Heartbeat

·Pinned

Guide to Non-Linear Activation Functions in Deep Learning

Non-linear activation functions that you need to know — Activation functions are equations or mathematical formulas that help us determine the output of a neural network. The main purpose of an activation function is to derive an output value based on the input value that is fed to a neuron. In deep learning, activation functions add non-linearity to the…

Activation Functions

7 min read

Guide to Non-Linear Activation Functions in Deep Learning
Guide to Non-Linear Activation Functions in Deep Learning
Activation Functions

7 min read


Published in

Heartbeat

·Pinned

Guide to Distance Metrics in Machine Learning Algorithms

Distance Metrics used in machine learning algorithms — Distance metrics play a very important role in machine learning. A number of machine learning algorithms, both supervised and unsupervised, use distance metrics to calculate the similarity between two data points. These distance metrics calculate mathematics-driven distance between various data points available in the dataset. …

Heartbeat

6 min read

Guide to Distance Metrics in Machine Learning Algorithms
Guide to Distance Metrics in Machine Learning Algorithms
Heartbeat

6 min read


Published in

Heartbeat

·Pinned

Guide to Activation Functions in Neural Networks

How to choose the best activation function for your deep learning model — Activation functions play an essential part in artificial neural networks as they decide whether a neuron should be activated or not. Activating a neuron determines whether the information that the neuron is receiving is relevant and if it should be used or ignored. Activation functions are mathematical equations that help…

Heartbeat

6 min read

Guide to Activation Functions in Neural Networks
Guide to Activation Functions in Neural Networks
Heartbeat

6 min read


Published in

Heartbeat

·Pinned

Techniques to Handle Imbalanced Data in Machine Learning

Different ways to handle imbalanced data for a classification problem — In the machine learning process, while dealing with classification problems, you’ve probably faced situations where the number of observations for one of the target class labels is significantly lower than the observations of other target classes. …

Heartbeat

6 min read

Techniques to Handle Imbalanced Data in Machine Learning
Techniques to Handle Imbalanced Data in Machine Learning
Heartbeat

6 min read


Published in

Heartbeat

·Pinned

Hyperparameter Tuning in Machine Learning Using GridSearchCV

Finding the optimal hyperparameters using grid search — Model parameters and model hyperparameters are two important things that we define while building a machine learning model. …

Heartbeat

5 min read

Hyperparameter Tuning in Machine Learning Using GridSearchCV
Hyperparameter Tuning in Machine Learning Using GridSearchCV
Heartbeat

5 min read


Published in

Better AI

·Updated May 13

Transfer Learning in Neural Network

A hands-on guide to transfer learning in deep learning — Transfer learning is a machine learning technique that allows us to use a pre-trained model as a starting point to develop a new model, rather than building and training a new machine learning model from scratch. The main goal of the transfer learning technique is to utilise the knowledge and…

Neural Networks

6 min read

Transfer Learning in Neural Network
Transfer Learning in Neural Network
Neural Networks

6 min read


Published in

Predict

·May 13

7 MacOS Applications That are Highly Useful but Underrated

Let’s discuss some useful MacOS apps that can make you more productive — Mac is known for its sleek design, powerful performance, and user-friendly interface, which makes it a popular choice for both personal and professional use. It is very intuitive with an easy-to-use interface, which makes it appealing to users who are not tech-savvy. If you have your own Apple device such…

Mac

4 min read

7 MacOS Applications That are Highly Useful but Underrated
7 MacOS Applications That are Highly Useful but Underrated
Mac

4 min read


Published in

Level Up Coding

·Mar 29

9 Python Code Snippets That Can be Used to Solve Everyday Problems

Must check these code snippets — Python is a versatile programming language that can be used to solve a wide variety of daily problems. Its versatility and ease of use make it a great choice for solving a wide variety of everyday problems. In this article, we will go through some examples that will show how…

Python

6 min read

9 Python Code Snippets That Can be Used to Solve Everyday Problems
9 Python Code Snippets That Can be Used to Solve Everyday Problems
Python

6 min read


Published in

Level Up Coding

·Jan 30

10 Pandas Functions That You Need to Know Today

Must know pandas library functions in python — Pandas is a library in Python that makes it easy to work with datasets. It provides tools to organize, analyze and clean up datasets. It helps us to sort, filter and make calculations on that data so that we can get the information we need. Pandas is widely used in…

Python

4 min read

10 Pandas Functions That You Need to Know Today
10 Pandas Functions That You Need to Know Today
Python

4 min read


Published in

Level Up Coding

·Jan 16

9 Python Code Refactoring Tips to Write Cleaner Code

Tips to make your code faster, cleaner, and maintainable — Code refactoring is one of the most interesting and important parts of your code. Refactoring your code not only makes your code more readable but also reduces the number of unnecessary lines. In this article, we will go through some best practices that will help you write Python code in…

Python

4 min read

9 Python Code Refactoring Tips to Write Cleaner Code
9 Python Code Refactoring Tips to Write Cleaner Code
Python

4 min read

Pralabh Saxena

Pralabh Saxena

573 Followers

Data Engineer | Data Science | Love to write and express. About me https://linktr.ee/pralabhsaxena

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