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Data-Driven Science @DrivenScience

Practice Your Data Science Skills

Joined April 2020
  • Tweets 928
  • Following 80
  • Followers 676
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Data-Driven Science@DrivenScience
29 Jul 2021
9 Best Python libraries for Machine Learning - Numpy - Scipy - Scikit-learn - Theano - TensorFlow - Keras - PyTorch - Pandas - Matplotlib Follow @DrivenScience #MachineLearning #Python
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🎯 Classification vs 📈 Regression in #MachineLearning: Classification: Predicting labels/categories. 🍎🍌 Regression: Estimating continuous values. 🏠💲 Key: Classification = Discrete outcomes. Regression = Continuous predictions. #DataScience #SupervisedLearning
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🔍 #NaïveBayes in a nutshell: A fast & simple #MachineLearning algorithm that predicts data point categories using Bayes' theorem. Perfect for text classification & high-dimensional datasets. But remember, it assumes feature independence, which can be its Achilles' heel. 🚀💡
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The #Perceptron: Inputs: Feature Values Weights: Importance of features Net Input: Sum of weight x feature Activation: Decides output (usually step function) Output: Result of activation Error: Gap between prediction & reality #NeuralNetworks #MLBasics
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🎯 Exploring Precision & Accuracy in #MachineLearning: High Precision High Accuracy = Gold Standard 🏆 High Precision Low Accuracy = Careful but Wrong ❌ Low Precision High Accuracy = Right but Over-Inclusive 📊 Low Precision Low Accuracy = Needs Attention ⚠️
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Yes, check the competition out! 🦾
abhishek
@abhi1thakur
26 Jul 2023
Final chance to participate in Movie Genre Prediction competition and win exciting prizes! Check it out here: huggingface.co/spaces/compet… 🚀
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Fun project indeed 🤘
abhishek
@abhi1thakur
8 Jul 2023
Weekend fun: huggingface.co/spaces/compet…
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Data-Driven Science retweeted
abhishek
@abhi1thakur
6 Jul 2023
huggingface.co/spaces/compet…

Movie Genre Prediction - a Hugging Face Space by competitions

Discover amazing ML apps made by the community

huggingface.co
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Navigating the #BigData revolution? Understand its 5Vs: 1️⃣Volume: Massive data generation 2️⃣Variety: Diverse data types 3️⃣Value: Transforming raw data into insights 4️⃣Velocity: Rapid data creation & processing 5️⃣Veracity: Ensuring data accuracy & reliability #DataScience
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🚀 Diving into #DeepLearning history with LeNet-5, the groundbreaking CNN architecture by Yann LeCun in '98. Its alternating Convolutional & Pooling layers, & Fully Connected layers revolutionized image recognition tasks. A gem to study for grasping the basics of CNNs! #AI #ML 🧠
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Hierarchical Cluster Analysis organizes complex data into clusters like a data family tree 🌳 No need to predefine clusters - it's all in the dendrogram 📊! Perfect for any field dealing with unlabeled data. #DataScience #HierarchicalClustering #AI #BigData #DataVisualization
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Sounds perfect 💪
abhishek
@abhi1thakur
17 Jun 2023
weekend project?huggingface.co/spaces/compet…
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We launched a new competition on Hugging Face: The Movie Genre Prediction Competition 🎥 👉 Click here to participate in this competition: huggingface.co/spaces/compet… Submission Deadline is July 31st, 2023 🔔 Join today! #competition #nlp #naturallanguageprocessing #huggingface
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Join this competition and apply your NLP skills 👍
abhishek
@abhi1thakur
10 Jun 2023
huggingface.co/spaces/compet…
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Diving into the world of #MachineLearning? Consider AdaBoost! This adaptive 'meta-estimator' forms a strong learner from many weak ones, learning from mistakes & improving with each step. A testament to 'Unity is Strength' in algorithm form! 🤖💪 #AdaBoost #DataScience #AI
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🔍 Exploring Density-Based Clustering in #MachineLearning. Unlike K-means, these algorithms discover arbitrary-shaped clusters based on dense regions, handling noise and outliers effectively. Two great examples: #DBSCAN & #OPTICS. Stay curious and keep innovating! #DataScience
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"Diving deep into #SentimentAnalysis in #MachineLearning! 🚀 Really impressed with VADER's nuanced understanding of social media language & Naive Bayes' efficiency with large datasets. Fascinating how these tools unveil the emotions hidden in text. #DataScience #NLP #AI"
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"Early Stopping" is a useful regularization tool to curb overfitting and improve model performance. Shines in real-world scenarios like Image Recognition and NLP, but mind the quality of your validation set! #AI #DataScience #EarlyStopping #NLP #ImageRecognition
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🔍 Diving into #MachineLearning: Regression! A versatile tool for predictive modeling. Whether predicting house prices or classifying data, regression helps reveal variable relationships. Let's appreciate these foundations! 🧠📊 #AI #DataScience #ML
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🌟 Tackling #Overfitting in #MachineLearning with L1 & L2 Regularization! 🌟 L1 (Lasso) promotes sparse models & feature selection, while L2 (Ridge) addresses multicollinearity & distributes feature impact evenly. Choose wisely to build robust, accurate models! 💪 #DataScience
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