Published:
Using Convolutional Neural Networks (CNNs), I trained models to classify dog breeds from images—first from scratch, then using transfer learning with VGG16 and ResNet50. The results? Explore the power of deep learning, transfer learning, and surprising model quirks (like predicting a human as a Black Russian Terrier). Full code available on GitHub.
Published:
Which league has the most attacking defenders? Which teams defied expectations or crumbled under pressure? Who carried their team single-handedly? Using five seasons of player data (2014–20) and advanced stats like xG, xA, and xGC, I uncover surprising trends in goals, assists, and team dependency. Data meets the beautiful game—dive in! Full code and data available on GitHub.
Published:
Using Convolutional Neural Networks (CNNs), I trained models to classify dog breeds from images—first from scratch, then using transfer learning with VGG16 and ResNet50. The results? Explore the power of deep learning, transfer learning, and surprising model quirks (like predicting a human as a Black Russian Terrier). Full code available on GitHub.
Published:
Which league has the most attacking defenders? Which teams defied expectations or crumbled under pressure? Who carried their team single-handedly? Using five seasons of player data (2014–20) and advanced stats like xG, xA, and xGC, I uncover surprising trends in goals, assists, and team dependency. Data meets the beautiful game—dive in! Full code and data available on GitHub.
Published:
Which league has the most attacking defenders? Which teams defied expectations or crumbled under pressure? Who carried their team single-handedly? Using five seasons of player data (2014–20) and advanced stats like xG, xA, and xGC, I uncover surprising trends in goals, assists, and team dependency. Data meets the beautiful game—dive in! Full code and data available on GitHub.
Published:
Using Convolutional Neural Networks (CNNs), I trained models to classify dog breeds from images—first from scratch, then using transfer learning with VGG16 and ResNet50. The results? Explore the power of deep learning, transfer learning, and surprising model quirks (like predicting a human as a Black Russian Terrier). Full code available on GitHub.