Enroll Course: https://www.udemy.com/course/fundamentals-of-machine-learning-hindi/
In the ever-evolving world of technology, Machine Learning (ML) stands out as a transformative force. For those looking to dive into this exciting field, especially those who prefer learning in Hindi and with Python, the ‘All-in-One:Machine Learning,DL,NLP,AWS Deply [Hindi][Python]’ course on Udemy is a fantastic option. This comprehensive program aims to cover a vast spectrum of ML concepts, making it accessible even for beginners with no prior ML knowledge.
The course begins with a solid foundation, starting with the fundamental ‘Introduction to Machine Learning’, covering its types and core principles. Setting up the environment is made easy with detailed guides on installing Anaconda and using popular tools like Spyder and Jupyter Notebook. A significant and highly practical segment of the course is dedicated to cloud deployment using AWS. Students learn to create and connect to EC2 instances, install necessary libraries, transfer files, and execute Python scripts on the cloud – an invaluable skill for real-world applications.
The curriculum then delves deep into data preprocessing, a crucial step in any ML project. Topics like handling null values, checking for correlated features, data molding, imputation, scaling, and encoding (Label and One-Hot) are covered thoroughly, ensuring students understand how to prepare their data effectively.
Supervised learning is explored extensively, covering both Regression and Classification. From simple and multiple linear regression, including cost function minimization techniques like Gradient Descent, to classification algorithms like Logistic Regression, K-Nearest Neighbors, and Naive Bayes, the course provides a robust understanding. The practical aspect of saving and loading ML models, along with evaluating classification performance using confusion matrices, is also highlighted.
Unsupervised learning is not left behind. Students will learn about clustering techniques such as K-Means, Hierarchical Clustering, and DBSCAN, along with methods for measuring cluster performance. Association rule mining with the Apriori algorithm is also a key takeaway.
A standout feature of this course is its focus on deploying ML models. The section on deploying models using Flask, including setting up Flask on AWS and handling requests and responses, is particularly commendable for its practical relevance.
Further expanding the scope, the course introduces non-linear supervised algorithms like Decision Trees and Support Vector Machines (SVMs), including advanced concepts like the Kernel Trick. Natural Language Processing (NLP) is covered with essential text preprocessing techniques like tokenization, stop words removal, N-grams, stemming, and vectorization methods like Count Vectorizer and TF-IDF. A case study on building a spam filter demonstrates these concepts in action.
Deep Learning is introduced with the basics of Artificial Neural Networks, hidden layers, and activation functions, along with forward and backward propagation. Regularization techniques like Lasso and Ridge regression are explained to combat overfitting, alongside dimensionality reduction methods like PCA and LDA.
Finally, ensemble methods such as Bagging (Random Forest) and Boosting (Gradient Boosting) are covered for both regression and classification tasks, offering students powerful tools to improve model performance.
Recommendation:
For anyone seeking a comprehensive and practical introduction to Machine Learning in Hindi, this Udemy course is highly recommended. Its A-Z coverage, hands-on approach with Python, and inclusion of cloud deployment and advanced topics like Deep Learning and NLP make it an excellent investment for aspiring data scientists and ML engineers.
Enroll Course: https://www.udemy.com/course/fundamentals-of-machine-learning-hindi/