TechNetzz | Top Python Machine Learning Tutorials

Deploy Machine Learning Models to Google Cloud, AWS, and Heroku

Python Machine Learning In the previous lesson, we explored how to serve machine learning models using Flask and FastAPI. These tools helped us create APIs that could run predictions locally. However, when it comes to real-world use, we need to deploy models to the cloud for better scalability and reliability. This... Read more

Deploy Machine Learning Models with Flask and FastAPI

Python Machine Learning In the previous lesson, we learned how to export trained machine learning models using TensorFlow and Scikit-Learn. This step is crucial because it allows us to save our models in a format that can be reused later. Now, we will take the next step: deploying these models as web services. This is... Read more

Export Machine Learning Models with TensorFlow & Scikit-Learn

Python Machine Learning In the last lesson, we explored text classification using BERT, a powerful transformer model that excels in understanding context in text data. We built a model that could classify text into categories, which is a common task in natural language processing. Now, it's time to take the next step:... Read more

Text Classification with BERT: A TensorFlow & Keras Guide

Python Machine Learning In the previous lesson, we explored sentiment analysis using Long Short-Term Memory (LSTM) networks. LSTMs are powerful for handling sequential data like text, but they have limits when it comes to understanding context over long sentences. This is where transformer models, like BERT, come into... Read more

Sentiment Analysis with LSTMs: Build NLP Models in TensorFlow

Python Machine Learning In the previous lesson, we explored text preprocessing techniques like tokenization and word embeddings, which are crucial for preparing text data for NLP tasks. These steps help convert raw text into a format that machine learning models can understand. Now, we'll dive into Lesson 9.2:... Read more

Text Preprocessing in NLP: Tokenization & Word Embeddings Explained

Python Machine Learning In the last lesson, we explored sequence modeling and text generation using LSTMs, where we learned how to build models that can predict the next word in a sequence. Now, we'll dive into the foundational step that comes before any NLP task: text preprocessing. This step is crucial because raw... Read more

Text Generation with LSTMs: Sequence Modeling in TensorFlow & Keras

Python Machine Learning In the previous lesson, we explored how LSTMs can predict stock prices by learning patterns in time-series data. Now, we'll dive into another exciting application of LSTMs: text generation. This lesson will teach you how to build an LSTM model that can generate text, a task that requires... Read more

Build LSTM Models for Stock Price Prediction with TensorFlow

Python Machine Learning In the last lesson, we explored the basics of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks. We learned how RNNs handle sequential data and why LSTMs are better at capturing long-term dependencies. We also discussed the structure of LSTM cells, which use gates to... Read more

Understanding RNNs and LSTMs for Time-Series Data

Python Machine Learning In the previous lesson, we explored Data Augmentation & Transfer Learning, which are key techniques for improving model performance using pre-trained models. These methods help us leverage existing knowledge to solve new problems, saving time and resources. Now, we'll dive into Recurrent Neural... Read more

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