Learn Data Science, Machine Learning and Artificial Intelligence
In this post, we will build an application using flask which will predict the house price based on the parameters influencing the house price. Later you can customize it for any model GUI designing. We will be using Flask which is widely used web framework for Machine Learning model deployment. There are other frameworks as well coming in the market like FastAPI but till today, flask is still the widely used and trusted framework over the machine learning community for model deployment.
In this video post I have explained about the below ML FAQ:
1. What is Gini
2. What is Gini Index
3. How to calculate Gini and Gini Index
4. How Gini Index helps to decide the Parent and Decision nodes in Decision Tree
In this video I will be explaining about the following ML questions:
1. How to Interpret Decision Tree
2. How splitting happens in the decision tree.
3. What is Entropy?
4. What in Information Gain?
5. How Information gain helps to decide the parent node and further node split?
When are you looking for the best way to express yourself without speaking, which technique comes to your mind? Yes, that’s right, it is an illustration. The illustration is one of the best ways to express a feeling or describe something. This technique has been started by our ancestors in the primitive age. It is a medium of explaining things easily so that anyone can understand. There are various types of comics you will find on the book store and online. Even you can read these tremendous African graphic novels. However, along with making comic stories and anime, there are other benefits of it. In technology, the comic is one of the top tools to teach and explain digital innovations and devices. In this article, you will find 7 fun comic illustrations that best describe machine learning.
In this we will learn from scratch how to implement decision tree using python. We will solve one classification problem and build the model from scratch. Following are the points we will be covering in this post:
Exploratory Data Analysis – EDA
Data Visualization
Data Pre-processing
Data Spliting- Stratified Sampling
Oversampling – SMOTE
Model Training
Fine Tuning
Hyper parameter Tuning
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ML FAQ Part 1
What is ROC-AUC curve and how to interpret it?
Explain Type I and Type II errors.
What is Precision and Recall?
What is F1 score?
What is the difference between r-square and adjusted r-square values?
Data Science Duniya 