Resource of free step by step video how to guides to get you started with machine learning.
Friday, January 15, 2021
AI Project Architecture, Machine Learning Project Architecture.
Machine Learning And Deep Learning Model Deployment Architecture Using API's. Ada boost, adjusted R square, AI, AlexNet, Anomaly detection, Architecture, Arima, Artificial Intelligence, AWS, Azure, Bagging, BeautifulSoup, Bias, Boosting, CNN, Computer Vision, Cost Function, Cross Validation, Curse of Dimensionality, Data Science, DBSCAN, Decision Tree, Decision tree regressor, Deep Learning, Dimensionality reduction, Django, EDA, Encoders and Decoders, Ensemble approach, exploratory data analysis, Facenet, fast ai, Faster R CNN, Flask, F-Score, Feature Selection, Feature Engineering, Data Cleaning, Handling Categorical Features, Handling Missing Values, Handling Duplicate Values, Handling Outliers, Removing Outliers, Data Scaling, Data Standardization, Data Normalization, Boosting, Bagging, ensemble learning ensemble models ensemble learning. ensemble methods, Model Selection, Model Training, Hyperparameter Tuning Hyperparameter Selection, Cross Validation Feature importance, Dimensionality Reduction, Handling Imbalance Data, Django jango Fast API Tensorflow JS, Tensorlite, Google Cloud Platform, Google Coral, GoogleNet, GPU, Gradient boost, Gradient descent, Hierarchical clustering, Jetwon nano, K Nearest Neighbor, Keras, K-Means, KNN, knn regressor, Lazy learners, LeNet, Linear Regression, Logistics regression, Long Short Term Memory, LSTM, Machine Learning, Matplotlib, ML, Model Deployment, mongodb, Naive bayes, Natural Language Processing, Neural Network, NLP, NumPy, OLS, Opencv, Ordinary Least Squares, Overfitting, Pandas, Paperspace, PCA, Performance, Performance Evaluation, plotly, polynomial Regression, Precision, Principal Component analysis, PyCaret, PyTorch, R square , Randon Forest, Recall, Recurrent Neural Networks, Reinforcement, ResNet, Ridge Regression, RNN, ROC curve, Sarima, Scikit Learn SciPy, Scrappy, seaborn, Semi-supervised, Spacy, Spark, Sqlite, SSD, Stacking, Statsmodels, Supervised, SVM, SVR, TensorFlow, TensorFlow Object Detection, Testing, Textblob, Theano, Time series forecasting, Training, Transfer Learning, underfitting, Unsupervised, Validation, Variance, VGGNet, Web Scrapping, Word2vec, XgBoost, YOLO, You Only Look Once,
Subscribe to:
Post Comments (Atom)
-
JavaやC++で作成された具体的なルールに従って動く従来のプログラムと違い、機械学習はデータからルール自体を推測するシステムです。機械学習は具体的にどのようなコードで構成されているでしょうか? 機械学習ゼロからヒーローへの第一部ではそのような疑問に応えるため、ガイドのチャー...
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
#minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command blocks. The n...
-
Using More Data - Deep Learning with Neural Networks and TensorFlow part 8 [Collection] Welcome to part eight of the Deep Learning with ...
-
Linear Algebra Tutorial on the Determinant of a Matrix 🤖Welcome to our Linear Algebra for AI tutorial! This tutorial is designed for both...
-
STUMPY is a robust and scalable Python library for computing a matrix profile, which can create valuable insights about our time series. STU...
-
❤️ Check out Fully Connected by Weights & Biases: https://wandb.me/papers 📝 The paper "Alias-Free GAN" is available here: h...
-
Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if we change t...
-
Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature of the p...
-
#ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane requirements...
No comments:
Post a Comment