Making Your Project Presentable: Last Touches for an Impressive Portfolio

Bonus lesson: Turning a Regression Problem into a Classification Problem

Is your model actually that good? Validating Machine Learning Models

Improve Machine Learning Model Performance with Tuning

Step-by-Step Preparing and Training a Machine Learning Model

Feature Engineering: Integrate a new data source into your dataset

Feature Engineering: Create new features using existing data

The Basics of Evaluating Machine Learning Projects

How to Train a Benchmark Model for your Machine Learning Project

Problem Definition and Data Preparation for a Real-Life Data Science Project

Extract Hour, Day, Month Info from Pandas DateTime

Fixing Incorrect Column Types in Pandas to Prepare Data for ML

Data Cleaning after Identifying Data Problems in Pandas

Data Exploration: Identifying Data Issues and Their Potential Causes

Using Data Visualization to Identify Data Problems

How Collecting Data Works on a Real-Life Data Science Project

Creating a GitHub Repository for a Data Science Project

Introduction to Jupyter Notebooks: explore the main functionalities

How to Set up a Data Science Development Environment

Hands-on Data Science course: Let's build a project together from scratch!

Key Concepts and Techniques for Natural Language Processing

How are training and tuning different?

Python vs. R comparison (by a die-hard Python fan)

Data Visualization Libraries For Python

Why do we split data into train test and validation sets?

How to fix missing values in your data

Quick explanation: One-hot encoding

How to Implement CNNs in Keras

CNN follow along calculations

Basics of Convolutional Neural Networks

Basics of Recurrent Neural Networks

LSTMs and GRUs

How to Implement RNNs in Keras

Training a Network for Better Performance

How to Tune a Neural Network

How to Understand What's Wrong with a Neural Network

Advanced Methods for Hyperparameter Tuning

Simple Methods for Hyperparameter Tuning

Tuning a Neural Network | Deciding on next steps to take

What is the Optimal Performance of a Neural Network?

How to Decide Whether Your Neural Network is Doing Well

How to Evaluate a Neural Network's Performance

Part 4: Tuning the Neural Network for Better Performance

Part 3: Training the Neural Network

Part 2: Best Settings to Initialize Your NN with

Part 1: Getting Ready to Build your First Advanced Neural Network

Part 5: Tips and Tricks on How to Initialize Your Neural Network

How to Make Neural Networks Train Faster on Keras

How to Use Learning Rate Scheduling for Neural Network Training

Pruning a neural Network for faster training times

How to select the correct optimizer for Neural Networks

How (and Why) to Use Mini-Batches in Neural Networks

Normalizing data for better Neural Network performance

How to Lower Neural Network Training Times

How to Solve Vanishing Gradients in Keras and Python

Gradient Clipping and How it Helps with Exploding Gradients in Neural Networks

How Does Batch Normalization Work

How to Choose an Activation Function for Neural Networks

How to Choose the Correct Initializer for your Neural Network

What is Vanishing/Exploding Gradients Problem in NNs