Python & Machine Learning for Financial Analysis

Python & Machine Learning for Financial Analysis

Master Python Programming Fundamentals and Harness the Power of ML to Solve Real-World Practical Applications in Finance

What you’ll learn

• Master Python 3 programming fundamentals for Data Science and Machine Learning with a focus on Finance.
• Understand how to leverage Python's power to apply key financial concepts such as calculating daily portfolio returns, risk, and Sharpe ratio.
• Understand the theory and intuition behind Capital Asset Pricing Model (CAPM), Markowitz portfolio optimization, and the efficient frontier.
• Apply Python to implement several trading strategies such as momentum-based and moving average trading strategies.
• Understand how to use Jupyter Notebooks for developing, presenting, and sharing Data Science projects.

Python & Machine Learning for Financial Analysis

The Complete Python &Machine Learning for Financial Analysis

Master Python Programming Fundamentals and Harness the Power of ML to Solve Real-World Practical Applications in Finance

What you’ll learn

• Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
• Understand how to leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns, risk and Sharpe ratio.
• Understand the theory and intuition behind Capital Asset Pricing Model (CAPM), Markowitz portfolio optimization, and efficient frontier.
• Apply Python to implement several trading strategies such as momentum-based and moving average trading strategies.

Python-Introduction to Data Science and Machine learning A-Z

Python-Introduction to Data Science and Machine learning A-Z

Python basics Learn Python for Data Science Python For Machine learning and Python Tips and tricks

What you’ll learn

• Uderstand the basics of python programming
• learning all the basic mathematical concepts
• Understand the basics of Data science and how to perform it using Python
• Learn to use different python tools specialisez for data science

Complete Machine Learning with R Studio - ML for 2020

Complete Machine Learning with R Studio – ML for 2020

Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language – R studio

What you’ll learn

• Learn how to solve real life problem using the Machine learning techniques
• Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
• Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc.

The Machine Learning Course 2020

The Machine Learning Course 2020

Learn and understand Machine Learning from scratch.

What you’ll learn

• Understanding Machine Learning
• Mathematics
• Statistics
• Artificial Neural Networks
• Supervised Learning

The Certification Course Of Machine Learning

The Certification Course Of Machine Learning

Start as a beginner and go all the way to learn and understand Machine Learning.

What you’ll learn

1. Multiclass, Ranking, and Complex Prediction Problems
2. Decision Trees
3. Nearest Neighbor
4. Decision Trees
5. Neural Networks

Machine Learning & Deep Learning in Python & R

Machine Learning & Deep Learning in Python & R

Learn about Machine Learning, Neural Networks, CNN, time series analysis and much more using Python & R studio

What you’ll learn

1. Learn how to solve real life problem using the Machine learning techniques
2. Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
3. Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc.
4. Understanding of basics of statistics and concepts of Machine Learning
5. How to do basic statistical operations and run ML models in Python

Machine Learning & Python & Data Science -140 Hours HD Video

Machine Learning & Python & Data Science -140 Hours HD Video

6 week Course

What you’ll learn

• Hypothesis Space and Inductive Bias
• Evaluation and Cross-Validation
• Linear Regression
• Learning Decision Tree
• Python Exercise on Decision Tree and Linear Regression
• and Much MUch More!!

Machine Learning From Basic to Advanced

Machine Learning From Basic to Advanced

Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included.

What you’ll learn

• Master Machine Learning on Python
• Make accurate predictions
• Make robust Machine Learning models
• Use Machine Learning for personal purpose
• Have a great intuition of many Machine Learning models
• Know which Machine Learning model to choose for each type of problem
• Use SciKit-Learn for Machine Learning Tasks
• Make predictions using linear regression, polynomial regression, and multiple regression
• Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc.

Requirements

• Some basic python programming experience.
• Basic understanding of python libraries like numpy, pasdas and matplotlib.
• Some high school mathematics.

Description

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:

• Part 1 – Data Preprocessing
• Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression.
• Part 3 – Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
• Part 4 – Clustering: K-Means, Hierarchical Clustering.

And as a bonus, this course includes Python code templates which you can download and use on your own projects.

Who this course is for:

• Anyone interested in Machine Learning.
• Students who have at least high school knowledge in math and who want to start learning Machine Learning.
• Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
• Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
• Any students in college who want to start a career in Data Science.
• Any people who want to create added value to their business by using powerful Machine Learning tools.

ENROLL NOW

Machine Learning & Deep Learning in Python & R

Machine Learning & Deep Learning in Python & R

Learn about Machine Learning, Neural Networks, CNN, time series analysis and much more using Python & R studio

What you’ll learn

• Learn how to solve real life problem using the Machine learning techniques
• Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
• Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc.
• Understanding of basics of statistics and concepts of Machine Learning

Machine Learning For Researchers

Machine Learning For Researchers

Learn Research Methods & Machine Learning

What you’ll learn

• Introduction to Research
• Finding a research problem
• Finalzing your objectives
• Research Methodology
• Introduction to Machine Learning:-  What is  Machine Learning  ?,
• Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs
• Artificial Neural networks [Theory and practical sessions – hands-on sessions]
• Support Vector Machines

AWS Certified Machine Learning – Specialty – Practice Tests

AWS Certified Machine Learning – Specialty – Practice Tests

Be an AWS Certified Machine Learning – Specialty (MLS-C01) – Practice Tests with real exam question

What you’ll learn

• Be an AWS Certified Machine Learning – Specialty (MLS-C01)

Requirements

• No technical experience is needed, we will use the theoretical layer
• Motivation and willingness to invest time and effort to pass this exam

Step by Step Guide to Machine Learning

Step by Step Guide to Machine Learning

A beginners guide to learn Machine Learning from scratch. Learn various algorithms and techniques using ML libraries.

What you’ll learn

• Learn how to use NumPy to do fast mathematical calculations
• Learn what is Machine Learning and Data Wrangling
• Learn how to use scikit-learn for data-preprocessing
• Learn different model selection and feature selections techniques
• Learn about cluster analysis and anomaly detection
• Learn about SVMs for classification, regression and outliers detection.