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amazonsagemakercourse

AWS Machine Learning Specialty Course

apache-spark-and-scala

best-practices-to-deploy-ml-model

Deploying a machine learning model is a crucial step in creating a production-level application. By following these best practices, you can ensure that your machine learning model is deployed successfully and can be used effectively in a production environment.

building-recommendation-systems-with-python

The repository provides a comprehensive guide to the theory, implementation, and evaluation of recommendation systems, as well as practical examples and case studies to help readers understand how to build and deploy recommendation systems in real-world applications

data-analysis-using-python

Learn to analyze data with Python. Here you will learn, Import data sets, Clean and prepare data for analysis, Manipulate pandas DataFrame, Summarize data, Build machine learning models using scikit-learn, Build data pipelines.

data-analysis-using-r

R is a powerful language used widely for data analysis and statistical computing. Learn how to investigate and summarize data sets using R and eventually create your own analysis.

data-visualization-with-python

data-visualization-with-r

deep-learning-with-tensorflow

Learn Deep Learning from this repository which help you to understand clearly about Deep Neural Network, SPL, MPL Algorithm, CNN, RNN, and RBM etc.

exploratory_data_analysis_using_latest_libraries-

There are many libraries available in Python for EDA, including pandas, numpy, matplotlib, seaborn, and plotly. Create this depository to keep up to date with the latest libraries and techniques.

heroku-deployment-demo

machine-learning-with-python

Machine learning is changing the world and if you want to be a part of the ML revolution, this is a great place to start! This repository serves as an excellent introduction to implementing machine learning algorithms in depth such as linear and logistic regression, decision tree, random forest, SVM, Naive Bayes, KNN, K-Mean Cluster, PCA, Time Series Analysis and so on.

machine-learning-with-r

This repository serves as an excellent introduction to implementing machine learning algorithms with R in depth such as linear and logistic regression, decision tree, random forest, SVM, Naive Bayes, KNN, K-Mean Cluster, PCA, Time Series Analysis and so on.

machine-learning-with-sparkmllib

This Spark MLlib repository will introduce you to Apache Spark's scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, etc.

natural-language-processing-nlp

This repository will provide an overview and working knowledge of Natural Language Processing (NLP), using Python’s Natural Language Toolkit (NLTK) library and with Keras.

python-for-beginners

Find Real Python’s Beginners Roadmap for Learning Python! We also offer a beginner’s level user guide, which uses interesting examples to help you learn programming and web development. Happy Coding!

python-for-data-scientists

This repository will offer several learning strategies and advanced study material along with the interesting use case and programs that will help jump start your journey of becoming a data scientist with python !!!

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

r-for-beginners

Learn R in simple and easy steps starting from basic to advanced concepts with examples. If you are trying to understand the R programming language as a beginner, this tutorial will give you enough understanding on almost all the concepts of the language from where you can take yourself to higher levels of expertise.

r-for-data-scientists

Learn the fundamentals of R programming, from reading and writing data to customizing visualizations and performing predictive analysis on data.

scala-essentials

Essential Scala depository is aimed at experienced developers at very beginning level.

sql-essentials

This repository helps you get started learning SQL as a beginner. My goal is to help you understand SQL, so you can take your database skills to the next level!

statistics-for-data-science-using-python

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.

statistics-for-data-science-using-r

Learn the core statistical concepts, followed by application of these concepts using R Studio with the a nice combination of theory and practice. Learn key statistical concepts and techniques like exploratory data analysis, correlation, regression, and inference.

time-series-analysis-guide-for-beginners

This repository is dedicated to helping beginners understand and master the fundamentals of time series analysis, a critical field in data science and statistics. Whether you're a student, data enthusiast, or aspiring data scientist, this repository is your one-stop resource to demystify time series data and build valuable skill