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Pedram Jahangiry
Pedram Jahangiry
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Module 2 -Part 2- Setting up Deep Forecasting environment basic Python timeseries
Module 2 -Part 1- Setting up Deep Forecasting environment platforms and python packages
Module 1- Part 4- Demystifying timeseries data and modeling Can we beat WallStreet?
Module 1- Part 3 Demystifying timeseries data and modeling classical vs ML vs DL modeling
Module 1- Part 2- Demystifying timeseries data and modeling forecasting strategies
Where to Find Materials for All My Courses
Module 1- Part 1- Demystifying timeseries data and modeling Basics
Your One-Stop Resource Guide Where to Find Course Materials for All My Courses
Welcome to the Deep Forecasting course Advanced Timeseries with Econometrics ML and DL
We Did It Pedram Jahangiry Wins Teacher of the Year 2024 at Utah State University
Module 12 - Python Part 2 Mastering Clustering with PyCaret - K-Modes & K-Prototypes Unveiled
Module 12- Python part1 Mastering Clustering techniques using Sklearn Kmeans Hierarchical
Module 12- Mastering Clustering in ML K-Means K-Modes K-Prototypes & Hierarchical Methods
Module 11- Python Mastering PCA & Kernel PCA in Python using Sklearn and pca packages
Module 11- Theory Eigenvalues Eigenvectors and Principle Component Analysis PCA and Kernel PCA
Module 10- Python 3 Mastering Machine Learning Boosting algorithms in Scikit Learn and Pycaret
Module 10- Theory 4 Timeseries challenges in machine learning Cross validation and Bootstrapping
Module 10- Theory 3 Advanced ML boosting techniques XGboost Catboost LightGBM
Module 10- Theory 2 Machine Learning Boosting techniques AdaBoost GBM and XGboost
Module 10- Python 1 Master Bagging & Random Forest REGRESSION in Python with Sklearn & PyCaret
Module 10- Theory 1 Mastering Bagging and Random Forest in Machine Learning
Module 10- Python 2 Master Bagging & Random Forest CLASSIFICATION in Python with Sklearn & PyCaret
Module 9- Python Mastering Decision Trees A Comprehensive Guide with Sklearn and PyCaret
Module 9- Theory Decision Trees CART Explained- Everything You Need to Master Them
Module 8- Python Mastering KNN in Python- A Complete Guide with Scikit-learn and PyCaret
Module 8- Theory KNN in Depth A Comprehensive Guide to Regression & Classification
Module 7- Theory 2- Classification metrics in machine learning
Module 7- Theory 1- The Fundamentals of Logistic Regression. Beyond Linear Probability Models
Module 7- Python- Logistic Regression in Action Classifying Data with Scikit-Learn and Pycaret
Module 6- Python Implementing Ridge Lasso and Elastic Net with Sklearn and Pycaret
Module 6- Theory Penalized Regressions Demystified Ridge Lasso and Elastic Net
Module 5- Python Linear Regression Machine Learning approach sklearn PyCaret
Module 5- Python Polynomial Regression Machine Learning approach Sklearn
Module 5- Theory Linear to Polynomial Mastering Regression Models in ML Theory Explained
Module 4- Part 1- The Anatomy of Machine Learning Models - what is Overfitting?
Module 4- Part 2- The Mechanics of ML models Unpacking How Machines Learn?
Module 3- Mastering Linear Regression in Python with Statsmodels A Step-by-Step Guide
Module 3- Understanding Linear Regression Through an Econometrics Lens
Module 2- Cracking data with Python Exploratory Data Analysis EDA
Module 2- Setting Up Your Python Environment for Machine Learning
Module 1- Introduction to Machine Learning
Time-Series Data prep for ML & DL Single and Multi-Output Forecasting forecasting market returns
Predicting the Unpredictable Can Deep Learning Beat Econometrics and ML in Stock Market Forecasts?
Module 7- Python1- Unlock the Power of Custom Transformers IMDB Text Classification in TensorFlow
Module 7- Part 1- The Essential Transformers Prerequisites Why attention is ALL you need
Module 7- Part 2- Unleash the Power of Transformers Architecture - Ultimate Deep Dive
Module 6- Python 2- NLP - IMDB Sentiment Analysis - Bag of Words vs Sequence Models in TensorFlow
Module 6- Python1- Master Multi-Feature Timeseries Forecasting with LSTM in TensorFlow
Module 6- part3- Natural Language Processing NLP How to prepare text data correctly?
Module 6- Part 1- Deep Sequence Modeling- what is RNN and why should we go beyond it?
