Suneel Patel's repositories
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.
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!
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.
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.
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.
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 !!!
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.
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.
R-for-Data-Scientists
Learn the fundamentals of R programming, from reading and writing data to customizing visualizations and performing predictive analysis on data.
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.
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.
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
AmazonSageMakerCourse
AWS Machine Learning Specialty Course
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
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.
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.
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!