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This course from Microsoft on edX covers the essential mathematical foundations for machine learning and AI using Python.

An in-depth introduction to machine learning, covering topics from linear models to deep learning. The syllabus includes on-line algorithms and support vector machines, with practical implementation in Python projects.

This course helps you learn essential foundational math concepts for AI and machine learning, like calculus, linear algebra, and statistics, using a hands-on approach with Python.

This course equips learners with the skills to build and train powerful deep-learning models using PyTorch. It includes an in-depth exploration of convolutional neural networks for image recognition and covers advanced training techniques like dropout and batch normalization, which are crucial for avoiding common pitfalls.

Welcome to the SG Learn Series targeted at Singapore-based learners picking up new skillsets and competencies. This course is an adaptation of the same course by Jose Marcial Portilla and is specially produced in collaboration with Jose for Singaporean learners. If you are a Singaporean, you are eligible for the CITREP+ funding scheme, terms and conditions apply. --------------- Note from Jose .... Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:Programming with Python Num Py with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visual

Learn the Most demanding language of industry with concept applied to Data Science, Machine Learning and AI Important topics  are covered such as Python Basic Concepts, Advance Concept, Python Crash Course, Python Libraries such as numpy, pandas, matplotlib, seaborn, Data Science Concept with Case Studies , Machine Learning and it's types, Artificial Intelligence with Case Studies This Course will design to understand Data Visualization and Data Analysis with  Machine Learning Algorithms with case Studies.  Data Analysis with Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered. The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered. Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered. The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered. Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered. Data Visualization and Analysis with ML using Python, Numpy Pandas, Matplotlib, Seaborn, Plotly & Scikit-Learn library This Course will design to understand Machine Learning Algorithms with case Studies using Scikit-Learn Library. The Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the trad

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine Learning is the most in-demand and Highest Paying job of 2017 and the same trend will follow for the coming years. With an average salary of $120,000 (Glassdoor and Indeed), Machine Learning will help you to get one of the top-paying jobs. This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science! At the end of the course you will be able to Master Machine Learning using Python Demystifying Artificial Intelligence, Machine Learning, Data Science Explore & Define a ML use caseML Business Solution Blueprint Explore Spyder, Pandas and Num PyImplement Data Engineering Exploratory Data Analysis Introduction to Statistics and Probability Distributions Learn Machine Learning Methodology Understand Supervised Learning Supervised Learning Implement Simple & Multiple Linear Regression Decision Trees Regression & Classification Model Evaluation Cross Validation, Hyperparameter Ensemble Modeling Random Forest & XG Boost Learning Machine Learning is a definite way to advance your career and will open doors to new Job opportunities. 100% MONEY-BACK GUARANTEE This course comes with a 30-day money back guarantee. If you're not happy, ask for a refund, all your money back, no questions asked. Feel forward to have a look at course description and demo videos and we look forward to see you inside.

Hello there,Welcome to the " Machine Learning & Data Science with Python, Kaggle & Pandas " Course Machine Learning A-Z course from zero with Python, Kaggle, Pandas and Numpy for data analysis with hands-on examples Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. Machine learning helps you stay ahead of new trends, technologies, and applications in this field.Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more. In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use. Machine learning is often a disruptive technology when applied to new industries and niches. Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes. With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions.It’s hard to imagine our lives without machine learning. Predictive texting, email filtering, and virtual personal assistants like Amazon’s Alexa and the i Phone’s Siri, are all technologies that function based on machine learning algorithms and mathematical models. Python, machine learning, django, python programming, machine learning python, python for beginners, data science. Kaggle, statistics, r, python data science, deep learning, python programming, django, machine learning a-z, data scientist, python for data science Pandas is an open source Python package that is most widely used for d

Welcome to our Machine Learning Projects course! This course is designed for individuals who want to gain hands-on experience in developing and implementing machine learning models. Throughout the course, you will learn the concepts and techniques necessary to build and evaluate machine-learning models using real-world datasets.We cover basics of machine learning, including supervised and unsupervised learning, and the types of problems that can be solved using these techniques. You will also learn about common machine learning algorithms, such as linear regression, k-nearest neighbors, and decision trees.ML Prerequisites Lectures Python Crash Course: It is an introductory level course that is designed to help learners quickly learn the basics of Python programming language.Numpy: It is a library in Python that provides support for large multi-dimensional arrays of homogeneous data types, and a large collection of high-level mathematical functions to operate on these arrays.Pandas: It is a library in Python that provides easy-to-use data structures and data analysis tools. It is built on top of Numpy and is widely used for data cleaning, transformation, and manipulation.Matplotlib: It is a plotting library in Python that provides a wide range of visualization tools and support for different types of plots. It is widely used for data exploration and visualization.Seaborn: It is a library built on top of Matplotlib that provides higher-level AP Is for easier and more attractive plotting. It is widely used for statistical data visualization.Plotly: It is an open-source library in Python that provides interactive and web-based visualizations. It supports a wide range of plots and is widely used for creating interactive dashboards and data visualization for the web.

You're looking for a complete Artificial Neural Network (ANNs) course that teaches you everything you need to create a Neural Network model in Python, right?You've found the right Neural Networks course!After completing this course you will be able to:Identify the business problem which can be solved using Neural network Models.Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc.Create Neural network models in Python using Keras and TensorFlow libraries and analyze their results.Confidently practice, discuss and understand Deep Learning concepts How this course will help you?A Verifiable Certificate of Completion is presented to all students who undertake this Neural networks course.If you are a business Analyst or an executive, or a student who wants to learn and apply Deep learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the most advanced concepts of Neural networks and their implementation in Python without getting too Mathematical.Why should you choose this course?This course covers all the steps that one should take to create a predictive model using Neural Networks.Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business.What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniqu

Hi all Its Jay I am a data scientist by profession and Instructor by passion I have around 4 years of experience as data scientist,  I started my career as analyst as gradually moved to data scientist hence  I can understand what are programming prerequisites for data scientist. This course is created for absolute beginners of data science and machine learning.  It covers all aspect of python languages required in data science machine learning and deep learning.

Get instant access to a 69-page Machine Learning workbook containing all the reference material Over 9 hours of clear and concise step-by-step instructions, practical lessons, and engagement Introduce yourself to our community of students in this course and tell us your goals Encouragement &amp; celebration of your progress: 25%, 50%, 75%, and then 100% when you get your certificate What will you get from doing this course?This course will help you develop Machine Learning skills for solving real-life problems in the new digital world. Machine Learning combines computer science and statistics to analyse raw real-time data, identify trends, and make predictions. You will explore key techniques and tools to build Machine Learning solutions for businesses. You don’t need to have any technical knowledge to learn these skills.What will you learn:What is Machine Learning Supervised Machine Learning Unsupervised Machine Learning Semi-Supervised Machine Learning Types of Supervised Learning: Classification Regression Types of Unsupervised Learning: Clustering Association Data Collection Data Preparing Selection of a Model Data Training and EvaluationHPT in Machine Learning Prediction in MLDPP in ML Need of DPP Steps in DPP Python Libraries Missing, Encoding, and Splitting Data in ML Python, Java, R,and C ++How to install python and anaconda?Interface of Jupyter Notebook Mathematics in Python Euler's Number and Variables Degree into Radians and Radians into Degrees in Python Printing Functions in Python Feature Scaling for ML<p