That's a wrap! Every day, I share and simply content around Python, Data Science, Machine Learning & Large Language Models. Find me → @Sumanth_077 Like/RT the first tweet and help this reach more people.
@sumanth_077
-
Predict Method Implementation with Binary Classification Threshold
By
–
Finally the predict method: It uses the trained model to make predictions based on input features. This method applies a threshold of 0.5 to make binary predictions, returning 1 for positive class predictions and 0 for negative class predictions.
-
Defining the Fit Method for Model Training with Gradient Descent
By
–
Define the "fit" method that does the training of model The method takes input data "X" and the corresponding target values "y" It also updates the weights and bias using gradient descent.
-
Computing Cross-Entropy Loss Cost Function for Classification
By
–
Compute Cost Function Next define the cost function, which is the cross-entropy loss, used to measure the error between predicted probabilities and actual labels.
-
Sigmoid Activation Function: Computing Class Probability in Machine Learning
By
–
Define Sigmoid Activation Function: This is used to compute the probability of the target class. Sigmoid function takes a linear combination of input features and returns values between 0 and 1, which represent the probability that a given sample belongs to the positive class.
-
Define LogisticRegression Class with Five Essential Methods
By
–
Define LogisticRegression class to encapsulate the functionality of Logistic Regression The class has 5 methods: __init__, sigmoid, compute_cost, fit and predict. First let's Initialize learning rate, epochs, weights and bias attributes using the __init__ method.
-
Logistic Regression Implementation from Scratch in Python
By
–
Logistic Regression Implemented from scratch in Python! Here is the step by step explanation with code:
-
Exploring Cleanlab Studio for Data Quality Management
By
–
Recently exploring the Cleanlab Studio and it's really good at handling the data quality. Thanks for sharing this Akshay!
-
Year Wrap-Up: Python, Data Science, ML & LLM Content Sharing
By
–
That's a wrap! Every day, I share and simply content around Python, Data Science, Machine Learning & Large Language Models. Find me → @Sumanth_077 Like/RT the first tweet and help this reach more people.
-
Modin Project Repository Checkout
By
–
Checkout the Project Repository here: https://
github.com/modin-project/
modin
…