Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. pythonawsdata-sciencemachine-learningcaffetheanobig-datasparkdeep-...
kaggle设置Python默认环境变量 kaggle data 前些天报名参加了 Kaggle 的 Data Cleaning 5天挑战,5天的任务如下: Day 1: Handling missing values Day 2: Data scaling and normalization Day 3: Cleaning and parsing dates Day 4: Fixing encoding errors (no more messed up text fields!) Day 5: Fixing inc...
Code for Kaggle Data Science Competitions. Contribute to jeongyoonlee/Kaggler development by creating an account on GitHub.
Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.
Explore and run machine learning code with Kaggle Notebooks | Using data from No attached data sources
Python Data Structures Every Programmer Should Know Mastering NumPy’s Universal Functions for Fast Array Computation Building Fun Projects with OpenAI Codex Get the FREE ebook 'The Great Big Natural Language Processing Primer' and 'The Complete Collection of Data Science Cheat Sheets' along with the...
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. ...
Kaggle also offers micro-courses on topics like machine learning, Python, deep learning, and more. These take about 3-7 hours to complete. Users can also participate in competitions to solve real-world data science problems. These give users the opportunity to put their skills to the test and...
Read stories about Data Science on the Data Science Dojo blog. Discover smart, unique perspectives on Data Science and the topics that matter most to you like Data Science, Artificial Intelligence, Deep Learning, Python, AI, Technology, Programming, Neur
One of my favorite parts of my job as a developer advocate is being able to help people get started in data science. I still remember when I made the transition from academia to data science almost 8