Machine Learning Fundamentals
Machine Learning Fundamentals is an exciting journey into Machine Learning in the world of finance. 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.
Single Course
Lifetime access to a single course
£79
One-time payment.
All Courses Access
3,784 videos across 427 playlists in our Boost plan.
£449
Billed annually.
All Courses & Company data
Advanced analytical tools for 7,000 firms in our Pro plan.
£699
Billed annually.
30-Day Money-Back Guarantee T&C apply
3000+ students enrolled
4.5
Hours
6
Topics
10
Practical Exercises
Machine Learning Fundamentals includes
- The ML Process
- Matplotlib and Seaborn
- A Few Quick Notes
- 5 countplot()
- Replace & Sparse Classes
- Spotting Outlier
- NaN Object
Dropping Null Values - Box Plots
- Saving Your Dataframe
- What are Regression Algorithms
- Real Relationships and Overfitting
- Regularizations
Decision Tree Ensemble Methods - Metadata
- Splitting Your Data
- Train_test_split()
- Unpacking Lists
- Progress Checkpoint
- Model Pipelines
- Progress Checkpoint
- Hyperparameter
- Tuning
- Aggregating Hyperparameter Grids
- Progress Checkpoints
- Cross Validation
- Creating Untrained Models
- Training and Tuning Models
- Model Evaluation
- Progress Checkpoint
- Visualizing Model Predictions
- Using Your Model
- Binary Classification
- Logistic Regression
- Decision Tree Classifiers
- Solution
- Metadata
- One Error
- Countplot of
- Investors
- Exploring Relationships
- Reviewing Your
- Results
- Feature Engineering
- Reviewing Tier Change
- Controlling for Demotions
- Analyzing Goldman Sachs
- Implot()
- Import Packages and Data
- Dummy Variables
- Remove Redundant Target
- Splitting Data
- Model Pipeline
- Validating Pipelines
- Hyperparameters
- Validating Hyperparameter Grids
- Cross Validation
- Fitting Untrainer Models
- AUROC
- Confusion Matrix
- Perfect AUROC
- Calculating AUROC
Machine Learning Fundamentals
| skills-certificate
Machine Learning Fundamentals
4.5
hours
10
Practical exercises
1
Exam
In Machine Learning Fundamentals, you will build machine learning algorithms from the ground up. Follow along with real-world case studies, as you walk through the process line-by-line. Once you have completed the course you will have a practical understanding of how machine learning is used in the finance industry, and you will be able to create new algorithms of your own from scratch.
Data Cleaning & Exploration
32 video minutes
3 excel exercises
Video minutes 32
Excel Exercises 3
Regression Algorithms
23 video minutes
0 excel exercises
Video minutes 23
Excel Exercises 0
Liquidity Regressor
55 video minutes
3 excel exercises
Video minutes 55
Excel Exercises 3
Classification Algorithms
6 video minutes
0 excel exercises
Video minutes 6
Excel Exercises 0
Investor Classifier in Python Part 1
29 video minutes
2 excel exercises
Video minutes 29
Excel Exercises 2
Investor Classifier in Python Part 2
24 video minutes
2 excel exercises
Video minutes 24
Excel Exercises 2
Learn from our expert instructors
Learn more about our full faculty
Wall Street Recognized Certification
Established on Wall Street, Financial Edge has taught at the biggest bulge-bracket firms since 2016, and now we offer that very same training online for you. It’s no secret that banking is fiercely competitive, which is why our Wall Street recognized certification is designed to let your employers know you have the skills to succeed.
What Our Students Say
Get Machine Learning Fundamentals Skills Certificate
Single Course
- Lifetime access
- Expert instructor support
Boost Plan
Includes full access to all certified courses.
- 266+ hours of instructor-led learning
- Search across 480+ playlists, 4000+ videos and Q&As
- Role-focused pathways
- Expert instructor support
Pro Plan
Full Felix access including all learning content and data features.
- Everything in the Boost plan
- Streamlined company data
- Current and historic filings for over 7000 companies
- Market and industry data
- Ready-to-use sector and transaction models
Frequently Asked Questions
What tech do I need?
Is it right for me?
Are Financial Edge's courses credible?
Will the Machine Learning Fundamentals help me get a job?
How long do I have to complete the Machine Learning Fundamentals ?
Are there any hidden costs?
What support will I get along the way?
What is the difference between a Felix subscription and buying a single course?
