Applied Machine Learning
Applied Machine Learning
Couldn't load pickup availability
99% Satisfaction Rate
- 30-day Money Back Guarantee
- Elite Professional Training
- Award-Winning Algorithms
- Trusted by Top Global Banks
Applied Machine Learning is an exciting journey into the real deal, Machine Learning in the world of finance. In this course, you’re going to navigate through several new useful libraries and Machine Learning techniques and then work to build two algorithms that have been used to advise Fortune 500 companies including McDonalds, Tiffanys, Gap, and more. * Some code adjusted to protect original IP *
Course Content
Course Content
Data Prep
Powerful machine learning algorithms require clean and relevant training data. Correct errors, eliminate sparse classes, and remove unwanted observations to provide your algorithm with premium fuel.
Build Your Pipelines
Model pipelines tell your algorithm how to process your data. Construct pipelines that standardize your data to a common scale, define competing model classes, and specify random states.
Train & Tune Your Algorithms
Optimizing your machine learning algorithm is like tuning a SpaceX rocket. Train competing models and tune your hyperparameters using cross-validation to maintain the integrity of your testing data.
Two Real World Case Studies
Build two real world machine learning algorithms that have been used to advise fortune 500 companies on hundreds of billions of dollars of transactions. The investor classifier and the liquidity regressor take you through real world application and leave you with the ability to Double the Accuracy of your predictive financial models.
Walk away with working algorithms
Our courses were designed for finance and investment banking professionals. Because PyFi’s material was built purely in the frame of a finance professional, you can easily repurpose the tools and algorithms you discover and build here to virtually any area of the finance industry you find yourself in. Just plug in the data from your work, and see your improved results.
-
The PyFi Guarantee
We offer a 100%, no questions asked, 30 day money-back guarantee to completely de-risk your investment. Enroll now, and if for any reason you aren't completely satisfied, send us an email and you'll get a full refund for up to one month after enrollment.
How does the Applied Machine Learning course work?
New Learning is constructed on prior knowledge
Your Excel skills give you a head start when it comes to learning Python. You are already a logical problem-solver and a systematic thinker. The framework you use to build Excel models are the same frameworks you will use to build algorithms. Python Fundamentals shows you how to bridge the gap.
Transform your Excel knowledge into Python expertise
Continue your journey with a strong foundation in Python after taking our Python Fundamentals course where we transform your existing Excel knowledge into Python expertise. In Applied Machine Learning we can continue building off
Developed with Professionals and Students
100% of our training content is developed collaboratively with real industry professionals and finance students to create the most interesting, relevant, and effective coding instruction on the market.
Real World Finance Examples
Because our training programs are designed for finance professionals, by finance professionals, you’ll learn Python with real industry examples and financial data. Our training is specific to finance professionals and Investment bankers and has been used by the top Investment Banks in the world since 2021.
What's Inside
Applied Machine Learning is approximately 3.5 hours in length and a student can generally complete the course in 6-10 hours when working through all of the exercises. Before beginning, you should have completed our Python Fundamentals course OR already be comfortable with the Python programming language. Your enrollment comes with lifetime access and support within the course via a comment section under each video lesson.
Data Cleaning & Exploration
Your machine learning models can only be as good as your training data. In this lesson, you will learn how to find and correct errors in your datasets using the data visualization packages Matplotlib and Seaborn.
Regression Algorithms
Learn about regression problems and 5 machine learning algorithms used to solve them. Those models are Lasso, Ridge, and Elastic Net, which fall under the category of Regularized Regression Models. The other models you will learn are Random Forest and Gradient Boosting which fall under the category of Decision Tree Ensemble Models. You will also learn about overfitting and the tools at your disposal to prevent it.
Liquidity Regressor Case Study
Build your first machine learning model from start to finish. The model you will construct is an altered version of a real machine learning algorithm used by top investment banks to advise companies such as: HP, McDonalds, Nordstrom, and many more.
Classification Algorithms
Learn about classification problems and some machine learning algorithms used to solve them.
By the end of this lesson, you will be familiar with
▪ Characteristics of Binary Classification Problems
▪ Regularized Logistic Regression Models
▪ Decision Tree Ensemble Classification Models
Investor Classifier Case Study Pt I
Explore the data for your second machine learning model. The model you will construct is an altered version of a real machine learning algorithm used by top investment banks to predict investor behavior when raising capital for large corporate clients.
Investor Classifier Cast Study Pt II
In this lesson, you will complete your second machine learning model. The model you will construct is an altered version of a real machine learning algorithm used by top investment banks to predict investor behavior when raising capital for large corporate clients.
Machine Learning Edge Blueprint Vol I and II Card Title
Receive the PDF version of the Python Fundamentals and Applied Machine Learning course as a bonus when you purchase Python Fundamentals and Applied Machine Learning as a bundle.
Professional Certification Exam
Verify Your Learning: Put your new Machine Learning skills to the test to see what you have learned and ensure retention.
Boost Your Resume: Add an impressive certification to your resume to demonstrate your new skills to employers.
What Our Customers Are Saying:
Jack V.
Debt Capital Markets Analyst
Brad B.
Private Equity Associate
Terrence Z.
Investment Banking Analyst
Gage C.
Mathematics Undergraduate
Ralph R.
Investment Banking Analyst
Will N.
Investment Banking Analyst
Trusted by the #1 Investment Bank in the USA and Canada
This course is perfect for...
Ready to Grow
Familiar with Excel
You are comfortable working with spreadsheets.
Early-Career Finance Professional
Finance Student
New to Python
Veteran finance professionals
By the end of the course you will...
Understand how Python and Machine Learning can be used in the world of finance to double the accuracy of your predictive models and gain efficiencies in your work not possible with Excel alone
Master the skill of distinguishing overfit models that promise more than they deliver. By understanding the nuances of overfitting, you will be equipped to refine your models to ensure they perform reliably in real-world financial scenarios, enhancing their predictability and your confidence in their forecasts.
Dive deep into the world of regularized regression and decision tree ensemble algorithms. This course highlights the strengths and limitations of each, guiding you to make informed decisions on which algorithm to deploy for your financial modeling tasks, ensuring optimal balance and performance.
Gain clarity on evaluating model performance with an in-depth understanding of the confusion matrix and its critical role in financial predictions. Learn how it intertwines with the ROC curve to give you a comprehensive view of your model's accuracy, allowing you to enhance predictive models with precision.
Learn to construct robust training and testing datasets and streamline your model development process with efficient pipelines. This skill set is crucial for developing models that are not only accurate but also scalable and adaptable to the fast-paced changes in the finance industry.
Elevate your data preparation skills with advanced techniques in cleaning, exploring, and visualizing financial datasets. These foundational steps are key to uncovering insights and trends that drive successful machine learning models, setting the stage for impactful financial analysis and predictions.
Unlock the potential of your financial datasets by learning how to engineer features that reveal deeper insights. Understand the conditional relationships between features to create new, powerful predictors that enhance the performance of your machine learning models in predicting market movements and trends.
Bring your financial prediction models across the finish line by mastering the art of building and finalizing machine learning classifiers. This course empowers you to not only construct but also fine-tune classifiers that stand up to the rigors of the finance world, ensuring your models are both accurate and resilient under market pressures.
Meet Your Instructor Zach Washam
While learning Python as an investment banker, Zach made an interesting observation: Python programming had a lot in common with the Excel models he made at work. By thinking of Python like Excel, Zach quickly learned the coding language and invented Wells Fargo Securities' first machine learning algorithm for investment banking and capital markets.
After submitting two algorithms for patent protection and winning Wells Fargo's 2018 "Local Sphere Innovation Award," Zach left investment banking to launch PyFi.
While CEO, Zach trained hundreds of students and finance professionals to code Python and develop their own Machine Learning algorithms, before stepping down from day to day operations to pursue other endeavours.
Applied Machine Learning
Applied Machine Learning is an exciting journey into the real deal, Machine Learning in the world of finance. In this course, you’re going to navigate through several new useful libraries and Machine Learning techniques and then work to build two algorithms that have been used to advise Fortune 500 companies including McDonalds, Tiffanys, Gap, and more.
Some code adjusted to protect original IP
- Elite Professional Training
- Award-Winning Algorithms
- Trusted by Top Global Banks
- 99% Satisfaction Rate
- 30-day Money Back Guarantee
