Data Science and Machine Learning

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Top 10 machine Learning algorithms for beginners 👇👇 1. Linear Regression: A simple algorithm used for predicting a continuous value based on one or more input features. 2. Logistic Regression: Used for binary classification problems, where the output is a binary value (0 or 1). 3. Decision Trees: A versatile algorithm that can be used for both classification and regression tasks, based on a tree-like structure of decisions. 4. Random Forest: An ensemble learning method that combines multiple decision trees to improve the accuracy and robustness of the model. 5. Support Vector Machines (SVM): Used for both classification and regression tasks, with the goal of finding the hyperplane that best separates the classes. 6. K-Nearest Neighbors (KNN): A simple algorithm that classifies a new data point based on the majority class of its k nearest neighbors in the feature space. 7. Naive Bayes: A probabilistic algorithm based on Bayes' theorem that is commonly used for text classification and spam filtering. 8. K-Means Clustering: An unsupervised learning algorithm used for clustering data points into k distinct groups based on similarity. 9. Principal Component Analysis (PCA): A dimensionality reduction technique used to reduce the number of features in a dataset while preserving the most important information. 10. Gradient Boosting Machines (GBM): An ensemble learning method that builds a series of weak learners to create a strong predictive model through iterative optimization. Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 Credits: https://t.me/datasciencefun Like if you need similar content 😄👍

🖥 Roadmap of free courses for learning Python and Machine learning. ▪Data Science ▪ AI/ML ▪ Web Dev 1. Start with this https://kaggle.com/learn/python 2. Take any one of these ❯ https://t.me/pythondevelopersindia/76 ❯ https://youtu.be/rfscVS0vtbw?si=WdvcwfYR3PaLiyJQ 3. Then take this https://netacad.com/courses/programming/pcap-programming-essentials-python 4. Attempt for this certification https://freecodecamp.org/learn/scientific-computing-with-python/ 5. Take it to next level ❯ Data Visualization https://kaggle.com/learn/data-visualization ❯ Machine Learning http://developers.google.com/machine-learning/crash-course https://t.me/datasciencefun/290 ❯ Deep Learning (TensorFlow) http://kaggle.com/learn/intro-to-deep-learning Please more reaction with our posts Credits: https://t.me/datasciencefree

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If you're into deep learning, then you know that students usually one of the two paths: - Computer vision - Natural language processing (NLP) If you're into NLP, here are 5 fundamental concepts you should know: